U.S. patent application number 12/853385 was filed with the patent office on 2010-12-02 for image processing apparatus, image processing method, and program.
This patent application is currently assigned to CANON KABUSHIKI KAISHA. Invention is credited to Fumihiro Goto, Fumitaka Goto, Yusuke Hashii, Masao Kato, Arata Miyagi, Mitsuhiro Ono, Tetsuya Suwa, Akitoshi Yamada.
Application Number | 20100302599 12/853385 |
Document ID | / |
Family ID | 39073675 |
Filed Date | 2010-12-02 |
United States Patent
Application |
20100302599 |
Kind Code |
A1 |
Goto; Fumihiro ; et
al. |
December 2, 2010 |
IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND
PROGRAM
Abstract
In order to provide an edge emphasis technique that can
eliminate image deterioration of a digital image, an image
processing apparatus includes a region setting unit which sets a
region including a pixel of interest, a brightness value derivation
unit which derives brightness values of the pixels, a first
derivative derivation unit which derives first derivatives of the
brightness values derived by the brightness value derivation unit,
an edge direction determination unit which determines an edge
direction of brightness at a position of the pixel of interest
based on the results of the first derivatives, a range
determination unit which determines a range, and a replacement unit
which replaces the pixel value of the pixel of interest.
Inventors: |
Goto; Fumihiro;
(Kawasaki-shi, JP) ; Goto; Fumitaka; (Tokyo,
JP) ; Kato; Masao; (Kawasaki-shi, JP) ;
Yamada; Akitoshi; (Yokohama-shi, JP) ; Suwa;
Tetsuya; (Yokohama-shi, JP) ; Ono; Mitsuhiro;
(Tokyo, JP) ; Miyagi; Arata; (Kawasaki-shi,
JP) ; Hashii; Yusuke; (Kawasaki-shi, JP) |
Correspondence
Address: |
FITZPATRICK CELLA HARPER & SCINTO
1290 Avenue of the Americas
NEW YORK
NY
10104-3800
US
|
Assignee: |
CANON KABUSHIKI KAISHA
Tokyo
JP
|
Family ID: |
39073675 |
Appl. No.: |
12/853385 |
Filed: |
August 10, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11771458 |
Jun 29, 2007 |
|
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12853385 |
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Current U.S.
Class: |
358/3.27 |
Current CPC
Class: |
H04N 1/2307 20130101;
H04N 1/4092 20130101; H04N 1/2323 20130101 |
Class at
Publication: |
358/3.27 |
International
Class: |
G06T 5/00 20060101
G06T005/00 |
Foreign Application Data
Date |
Code |
Application Number |
Jul 4, 2006 |
JP |
2006-184845 |
Claims
1. An image processing apparatus for processing image data to be
printed on a print medium by an image printing unit, comprising: a
setting unit adapted to set a print characteristic on the print
medium in the image printing unit; a region setting unit adapted to
set a region configured by a plurality of pixels including a pixel
of interest; a brightness value derivation unit adapted to derive
brightness values of the pixels in the region; a first derivative
derivation unit adapted to derive first derivatives of the
brightness values derived by said brightness value derivation unit
for a plurality of pixel sequences in different directions, which
include the pixel of interest; an edge direction determination unit
adapted to determine an edge direction of brightness at a position
of the pixel of interest based on the results of the first
derivatives at positions of the pixel of interest in the respective
pixel sequences derived by said first derivative derivation unit;
an emphasis level determination unit adapted to determine an
emphasis level of a pixel value based on the print characteristic
and the first derivatives at respective positions of a plurality of
pixels which line up in the edge direction determined by said edge
direction determination unit; and a replacement unit adapted to
calculate second derivatives of brightness values at respective
positions of the plurality of pixels which line up in the edge
direction determined by said edge direction determination unit, to
replace a pixel value of the pixel of interest by a pixel value
obtained by adding the emphasis level to a pixel value of a pixel
which has a minimum brightness value in the pixel sequence when the
second derivative at the position of the pixel of interest assumes
a positive value, and to replace a pixel value of the pixel of
interest by a pixel value obtained by adding the emphasis level to
a pixel value of a pixel which has a maximum brightness value in
the pixel sequence when the second derivative at the position of
the pixel of interest assumes a negative value, wherein said
replacement unit adjust the calculated second derivatives of
brightness values in accordance with the print characteristic on
the print medium set by said setting unit, and wherein said
emphasis level determination unit comprises: a fluctuation count
derivation unit adapted to derive a fluctuation count of brightness
values based on the first derivatives at the respective positions
of the plurality of pixels which line up in the edge direction; and
a fluctuation amount derivation unit adapted to derive a
fluctuation amount of brightness values based on the first
derivatives at the respective positions of the plurality of pixels
which line up in the edge direction, and wherein said emphasis
level determination unit determines the emphasis level of the pixel
value based on at least one of the fluctuation count and the
fluctuation amount, and wherein said emphasis level determination
unit comprises a second comparison unit adapted to compare the
fluctuation count with a third threshold and a fourth threshold
larger than the third threshold, sets the emphasis level to be a
designated minimum value when the fluctuation count is smaller than
the third threshold, sets the emphasis level to a designated
maximum value when the fluctuation count is larger than the fourth
threshold, and sets the emphasis level by linear interpolation
using the maximum value and the minimum value when the fluctuation
count is larger than the third threshold and is smaller than the
fourth threshold.
2. An image processing apparatus for processing image data to be
printed on a print medium by an image printing unit, comprising: a
setting unit adapted to set a print characteristic on the print
medium in the image printing unit; a region setting unit adapted to
set a region configured by a plurality of pixels including a pixel
of interest; a brightness value derivation unit adapted to derive
brightness values of the pixels in the region; a first derivative
derivation unit adapted to derive first derivatives of the
brightness values derived by said brightness value derivation unit
for a plurality of pixel sequences in different directions, which
include the pixel of interest; an edge direction determination unit
adapted to determine an edge direction of brightness at a position
of the pixel of interest based on the results of the first
derivatives at positions of the pixel of interest in the respective
pixel sequences derived by said first derivative derivation unit;
an emphasis level determination unit adapted to determine an
emphasis level of a pixel value based on the print characteristic
and the first derivatives at respective positions of a plurality of
pixels which line up in the edge direction determined by said edge
direction determination unit; and a replacement unit adapted to
calculate second derivatives of brightness values at respective
positions of the plurality of pixels which line up in the edge
direction determined by said edge direction determination unit, to
replace a pixel value of the pixel of interest by a pixel value
obtained by adding the emphasis level to a pixel value of a pixel
which has a minimum brightness value in the pixel sequence when the
second derivative at the position of the pixel of interest assumes
a positive value, and to replace a pixel value of the pixel of
interest by a pixel value obtained by adding the emphasis level to
a pixel value of a pixel which has a maximum brightness value in
the pixel sequence when the second derivative at the position of
the pixel of interest assumes a negative value, wherein said
replacement unit adjust the calculated second derivatives of
brightness values in accordance with the print characteristic on
the print medium set by said setting unit, and wherein the image
data includes a character image, and the print characteristic is a
designation of a line width of a character to be printed on the
print medium.
3. An image processing apparatus for processing image data,
comprising: a region setting unit adapted to set a region
configured by a plurality of pixels including a pixel of interest;
a determination unit adapted to determine a change characteristic
of an image associated with the pixel of interest using the
plurality of pixels in the set region; a print characteristic
setting unit adapted to set a print characteristic on a print
medium by a printing unit; and a modification unit adapted to
modify the pixel of interest using the pixels in the region set by
said region setting unit, and to correct a value of the modified
pixel of interest based on the set print characteristic.
4. The apparatus according to claim 3, wherein the change
characteristic includes a fluctuation amount and a fluctuation
count of brightness values of the plurality of pixels in the
region, and said modification unit replaces a color of the pixel of
interest by a color calculated using a pixel having a maximum
brightness value or a minimum brightness value in the region in
accordance with a fluctuation acceleration, and corrects the
fluctuation acceleration as the correction.
5. An image processing method for processing image data,
comprising: a region setting step of setting a region configured by
a plurality of pixels including a pixel of interest; a
determination step of determining a change characteristic of an
image associated with the pixel of interest using the plurality of
pixels in the set region; a print characteristic setting step of
setting a print characteristic on a print medium by a printing
unit; and a modification step of modifying the pixel of interest
using the pixels in the region set by said region setting unit, and
correcting a value of the modified pixel of interest based on the
set print characteristic.
6. The method according to claim 5, wherein the change
characteristic includes a fluctuation amount and a fluctuation
count of brightness values of the plurality of pixels in the
region, and in the modification step, a color of the pixel of
interest is replaced by a color calculated using a pixel having a
maximum brightness value or a minimum brightness value in the
region in accordance with a fluctuation acceleration, and the
fluctuation acceleration is corrected as the correction.
7. A non-transitory computer-readable storage medium, storing, in
executable form, a program for making a computer execute processing
of image data, said program comprising: a program code for
implementing a region setting step of setting a region configured
by a plurality of pixels including a pixel of interest; a program
code for implementing a determination step of determining a change
characteristic of an image associated with the pixel of interest
using the plurality of pixels in the set region; a program code for
implementing a print characteristic setting step of setting a print
characteristic on a print medium by a printing unit; and a program
code for implementing a modification step of modifying the pixel of
interest using the pixels in the region set by said region setting
unit, and correcting a value of the modified pixel of interest
based on the set print characteristic.
8. The non-transitory computer-readable medium according to claim
7, wherein the change characteristic includes a fluctuation amount
and a fluctuation count of brightness values of the plurality of
pixels in the region, and the program code for implementing the
modification step replaces a color of the pixel of interest by a
color calculated using a pixel having a maximum brightness value or
a minimum brightness value in the region in accordance with a
fluctuation acceleration, and corrects the fluctuation acceleration
as the correction.
Description
BACKGROUND OF THE INVENTION
[0001] This application is a continuation of A. N. 11/771,458,
filed on Jun. 29, 2007, claims benefit of the filing date of that
application under 35 U.S.C. .sctn.120, and claims benefit under 35
U.S.C. .sctn.119 of Japanese patent Application 184845/2006, filed
Jul. 4, 2006. The entire contents of each of the mentioned earlier
applications are incorporated herein by reference.
FIELD OF THE INVENTION
[0002] The present invention relates to an image processing
technique and, more particularly, to an edge emphasis technique of
a digital image.
DESCRIPTION OF THE RELATED ART
[0003] A copying machine which optically scans a document image and
prints a scanned image on a print medium such as a paper sheet or
the like is known. In general, the edge of an image optically
scanned by a scanning unit (scanner) of a copying machine is
smoother than that of a document image. For this reason, an image
with poor sharpness is output when the scanned image is printed on
a print medium intact. Hence, a technique for applying edge
emphasis processing to image data obtained after scanning a
document image is known. However, in general, upon applying the
edge emphasis processing, moire is emphasized together. To prevent
this problem, the following technique is known. That is, this
technique uses image region separation which separates scanned
image data into two regions, that is, a text region and a halftone
region, and applies edge emphasis processing to the text region and
smoothing processing to the halftone region to attain enhancement
of sharpness and a reduction of moire at the same time. However, if
a determination error occurs in image region separation, the
smoothing processing may be applied to a text region, and the edge
emphasis may be applied to a halftone region, thus deteriorating an
image. Depending on the precision of image region separation, for
example, a part of a character may be determined to be a text
region, and the remaining part of the character may be determined
to be a halftone region. In this case, switching of the edge
emphasis and smoothing processes occurs in one character. Such
switching considerably impairs an image.
[0004] Japanese Patent No. 3099354 (reference 1) discloses a
technique that continuously sets an edge emphasis level according
to an edge amount. With this technique, adaptive edge emphasis
according to the edge amount can be applied and can eliminate image
deterioration. Japanese Patent Laid-Open No. 2002-77623 (reference
2) discloses a technique that adaptively sets an edge emphasis
level according to an edge amount, and disables the adaptive
setting for a halftone region. With this technique, adaptive edge
emphasis according to the edge amount can be applied, and edge
emphasis of the halftone region can be reduced. Furthermore,
Japanese Patent No. 3472094 (reference 3) discloses a technique
that separates an image into multiple regions including a text
region, photo region, and halftone region according to the degree
of coupling and density difference of black pixels. With this
technique, more flexible image region separation can be
implemented.
[0005] In general, upon applying the edge emphasis processing,
overshoot and undershoot occur at an edge part. FIG. 14 illustrates
the edge emphasis processing result using an unsharp mask that
adjusts an emphasis level according to an edge amount. Referring to
FIG. 14, white dots 1401 represent brightness levels of an original
image at respective pixel positions, and black dots 1402 represent
brightness levels at the respective pixel positions, which are
converted by:
S'=S+K*(S-U) (1)
where S is an image signal of a pixel of interest, U is the
weighted average value of the image signal around the pixel of
interest, and K is a value generated based on the type and edge
amount of an image which is separated by image region separation.
In FIG. 14, two pixels each before and after the pixel of interest
are used as reference pixels, and equation (1) is applied for the
sake of descriptive convenience. As shown in FIG. 14, overshoot and
undershoot occur in the edge shape after the edge emphasis. When
this processing result is output using a high-resolution,
multi-gradation output apparatus, even overshoot and undershoot are
accurately expressed, and an image is output with a bordered edge
part.
[0006] Since a conventional output apparatus has a low print
resolution, overshoot and undershoot of the edge part are
inconspicuous, and a satisfactory output image is obtained.
However, upon advent of high-resolution, multi-gradation output
apparatuses in recent years, overshoot and undershoot of the edge
part are recognized as bordering of the edge part, thus leading to
image deterioration.
[0007] Hence, Japanese Patent No. 2620368 (reference 4) discloses
an edge processing technique that replaces the pixel of interest by
neighbor pixels. More specifically, it is checked if the pixel of
interest is convex upward or downward, or has any other shape in
the distribution pattern of an image signal. Based on the checking
result, the following processes are done: if the pixel of interest
is convex upward, the pixel of interest is replaced by a maximum
value in a neighbor region; if the pixel of interest is convex
downward, the pixel of interest is replaced by a minimum value in
the neighbor region; otherwise, the pixel of interest is replaced
by the average value or the value of the pixel of interest.
[0008] However, in the technique disclosed in reference 1, an edge
emphasis level is set focusing on the fluctuation amount of an edge
(edge amount). For this reason, a large edge emphasis level is set
for a halftone region having the same fluctuation amount as a text
region, and moire is also emphasized, thus deteriorating an
image.
[0009] In the technique disclosed in reference 2, an edge emphasis
level is similarly set focusing on an edge amount. However, since
this technique also focuses on a halftone cycle (fluctuation
count), and disables the adaptive edge emphasis level setting based
on the halftone cycle (fluctuation count), edge emphasis on a
halftone region can be stopped, thus reducing moire emphasis.
However, although the edge emphasis level is adaptively set up to a
certain fluctuation count in accordance with the edge amount, when
the certain fluctuation count is reached, the edge emphasis level
setting is disabled irrespective of the edge amount. For this
reason, switching of the processes occurs at the certain
fluctuation count, thus deteriorating an image.
[0010] The technique disclosed in reference 3 focuses on a
fluctuation count, since the edge amount of an image signal
decreases with increasing degree of coupling of black pixels. Also,
this technique focuses on the edge amount since the density
difference of black pixels is the edge amount of an image signal.
Three or more values are set for both the fluctuation count and
edge amount to improve separation precision upon separating an
image region into multiple regions including at least a text
region, photo region, and halftone region by image region
separation. However, adaptive separation according to the
fluctuation count and edge amount, and adaptive processing
intensities are not applied, and adaptive processes cannot be made
according to the fluctuation count or edge amount. Hence, switching
of the processes occurs, deteriorating an image and thus posing a
problem.
[0011] In the technique disclosed in reference 4, the edge emphasis
effect can be obtained by setting a region other than an upward or
downward convex region. However, since the same processing is also
applied to a halftone region, the aforementioned moire emphasis is
done together, thus posing a problem.
SUMMARY OF THE INVENTION
[0012] The present invention has been made in consideration of the
aforementioned problems, and has as its object to solve at least
one of the aforementioned problems.
[0013] According to one aspect of the present invention, an image
processing apparatus for processing image data, comprising: a
region setting unit adapted to set a region configured by a
plurality of pixels including a pixel of interest; a brightness
value derivation unit adapted to derive brightness values of the
pixels in the region; a first derivative derivation unit adapted to
derive first derivatives of the brightness values derived by the
brightness value derivation unit for a plurality of pixel sequences
in different directions, which include the pixel of interest; an
edge direction determination unit adapted to determine an edge
direction of brightness at a position of the pixel of interest
based on the results of the first derivatives at positions of the
pixel of interest in the respective pixel sequences derived by the
first derivative derivation unit; a range determination unit
adapted to determine a pixel sequence range, which is to undergo
pixel value replacement, based on the first derivatives at
respective positions of a plurality of pixels which line up in the
edge direction determined by the edge direction determination unit;
and a replacement unit adapted to calculate second derivatives of
brightness values along a lineup direction of the pixels in the
pixel sequence range, to replace a pixel value of the pixel of
interest by a pixel value of a pixel which has a minimum brightness
value in the pixel sequence range when the second derivative at the
position of the pixel of interest assumes a positive value, and to
replace a pixel value of the pixel of interest by a pixel value of
a pixel which has a maximum brightness value in the pixel sequence
range when the second derivative at the position of the pixel of
interest assumes a negative value.
[0014] According to another aspect of the present invention, an
image processing apparatus for processing image data, comprising:
an image type acceptance unit adapted to accept a type of image
data from a user; a brightness value derivation unit adapted to
derive brightness values of pixels in the image data; a range
determination unit adapted to determine a pixel sequence range,
which is to undergo pixel value replacement, based on the type; and
a replacement unit adapted to calculate second derivatives of
brightness values along a lineup direction of the pixels in the
pixel sequence range, to replace a pixel value of the pixel of
interest by a pixel value of a pixel which has a minimum brightness
value in the pixel sequence range when the second derivative at the
position of the pixel of interest assumes a positive value, and to
replace a pixel value of the pixel of interest by a pixel value of
a pixel which has a maximum brightness value in the pixel sequence
range when the second derivative at the position of the pixel of
interest assumes a negative value.
[0015] According to still another aspect of the present invention,
an image processing method for processing image data, comprising: a
region setting step of setting a region configured by a plurality
of pixels including a pixel of interest; a brightness value
derivation step of deriving brightness values of the pixels in the
region; a first derivative derivation step of deriving first
derivatives of the brightness values derived in the brightness
value derivation step for a plurality of pixel sequences in
different directions, which include the pixel of interest; an edge
direction determination step of determining an edge direction of
brightness at a position of the pixel of interest based on the
results of the first derivatives at positions of the pixel of
interest in the respective pixel sequences derived in the first
derivative derivation step; a range determination step of
determining a pixel sequence range, which is to undergo pixel value
replacement, based on the first derivatives at respective positions
of a plurality of pixels which line up in the edge direction
determined in the edge direction determination step; and a
replacement step of calculating second derivatives of brightness
values along a lineup direction of the pixels in the pixel sequence
range, replacing a pixel value of the pixel of interest by a pixel
value of a pixel which has a minimum brightness value in the pixel
sequence range when the second derivative at the position of the
pixel of interest assumes a positive value, and replacing a pixel
value of the pixel of interest by a pixel value of a pixel which
has a maximum brightness value in the pixel sequence range when the
second derivative at the position of the pixel of interest assumes
a negative value.
[0016] According to yet another aspect of the present invention, an
image processing program stored in a computer-readable storage
medium, comprising: a program code for implementing a region
setting step of setting a region configured by a plurality of
pixels including a pixel of interest; a program code for
implementing a brightness value derivation step of deriving
brightness values of the pixels in the region; a program code for
implementing a first derivative derivation step of deriving first
derivatives of the brightness values derived in the brightness
value derivation step for a plurality of pixel sequences in
different directions, which include the pixel of interest; a
program code for implementing an edge direction determination step
of determining an edge direction of brightness at a position of the
pixel of interest based on the results of the first derivatives at
positions of the pixel of interest in the respective pixel
sequences derived in the first derivative derivation step; a
program code for implementing a range determination step of
determining a pixel sequence range, which is to undergo pixel value
replacement, based on the first derivatives at respective positions
of a plurality of pixels which line up in the edge direction
determined in the edge direction determination step; and a program
code for implementing a replacement step of calculating second
derivatives of brightness values along a lineup direction of the
pixels in the pixel sequence range, replacing a pixel value of the
pixel of interest by a pixel value of a pixel which has a minimum
brightness value in the pixel sequence range when the second
derivative at the position of the pixel of interest assumes a
positive value, and replacing a pixel value of the pixel of
interest by a pixel value of a pixel which has a maximum brightness
value in the pixel sequence range when the second derivative at the
position of the pixel of interest assumes a negative value.
[0017] According to still yet another aspect of the present
invention, an image processing apparatus for processing image data,
comprising: an attribute determination unit adapted to determine an
attribute of an image in association with a pixel of interest; a
region setting unit adapted to set a region configured by a
plurality of pixels, which include the pixel of interest, and the
number of which is set according to the determination result of the
attribute determination unit; and a modification unit adapted to
modify the pixel of interest using the pixels in the region set by
the region setting unit.
[0018] According to yet still another aspect of the present
invention, an image processing method for processing image data,
comprising: an attribute determination step of determining an
attribute of an image in association with a pixel of interest; a
region setting step of setting a region configured by a plurality
of pixels, which include the pixel of interest, and the number of
which is set according to the determination result in the attribute
determination step; and a modification step of modify the pixel of
interest using the pixels in the region set in the region setting
step.
[0019] According to still yet another aspect of the present
invention, an image processing program stored in a
computer-readable storage medium, comprising: a program code for
implementing an attribute determination step of determining an
attribute of an image in association with a pixel of interest; a
program code for a region setting step of setting a region
configured by a plurality of pixels, which include the pixel of
interest, and the number of which is set according to the
determination result in the attribute determination step; and a
program code for a modification step of modifying the pixel of
interest using the pixels in the region set in the region setting
step.
[0020] According to the present invention, an edge emphasis
technique that can eliminate image deterioration of a digital image
can be provided.
[0021] Further features of the present invention will become
apparent from the following description of exemplary embodiments
(with reference to the attached drawings).
BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The accompanying drawings, which are incorporated in and
constitute a part of the specification, illustrate embodiments of
the invention and, together with the description, serve to explain
the principles of the invention.
[0023] FIG. 1 shows schematic perspective views of a multi function
printer (MFP) according to the first embodiment;
[0024] FIG. 2 is a block diagram showing the internal arrangement
of the MFP;
[0025] FIG. 3 is a flowchart of the overall processing to be
executed by an image processor of the MFP;
[0026] FIG. 4 is a view for explaining a processing unit of image
processes upon execution of the image processes;
[0027] FIG. 5 is a flowchart for explaining the operation for
shifting a processing unit;
[0028] FIGS. 6A and 6B are views illustrating a range of reflected
light which comes from a document and enters one pixel of an image
sensing element;
[0029] FIG. 7 is a detailed flowchart of an edge processing
operation;
[0030] FIGS. 8A and 8B are graphs illustrating changes in
brightness value, first derivative, and second derivative for two
different patterns;
[0031] FIG. 9 is a view for explaining pixel value extraction from
pixel sequences in four directions;
[0032] FIG. 10 is a view for explaining derivation of a first
derivative (Grd);
[0033] FIG. 11 shows graphs for explaining a fluctuation count;
[0034] FIG. 12 shows graphs for explaining an edge threshold and
smoothing threshold;
[0035] FIG. 13 shows graphs for explaining edge intensity
settings;
[0036] FIG. 14 is a graph showing the edge emphasis processing
result of the prior art;
[0037] FIG. 15 is a graph for explaining the derivation sequence of
pixel positions with maximum L and minimum L (reference range=5
pixels);
[0038] FIG. 16 is a graph for explaining the derivation sequence of
pixel positions with maximum L and minimum L (reference range=6
pixels);
[0039] FIG. 17 shows graphs of the edge emphasis processing results
when a replacement pixel reference range is changed;
[0040] FIG. 18 shows graphs of the edge emphasis results when the
numbers of pixels of the reference range are set to be even
numbers; and
[0041] FIG. 19 is a table for explaining a determination method of
a replacement pixel position.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0042] Preferred exemplary embodiments of the present invention
will be described in detail hereinafter with reference to the
accompanying drawings. Note that building components described in
these embodiments are merely examples, and they do not limit the
scope of the invention.
First Embodiment
[0043] As the first embodiment of an image processing apparatus
according to the present invention, an MFP (Multi Function Printer)
will be exemplified below. In the following description, the
apparatus arrangement and schematic operation of the MFP as a
precondition will be explained first, and characteristic features
of the present invention will then be explained in detail.
<Arrangement of MFP>
[0044] FIG. 1 shows schematic perspective views of a multi function
printer (to be referred to as an MFP hereinafter) according to the
first embodiment.
[0045] An MFP 100 comprises a function of printing data received
from a host computer (PC) as a normal PC printer, and a function of
scanning a document image as a scanner. Furthermore, functions as
the MFP alone include a copy function of printing an image scanned
by the scanner using the printer, a function of printing image data
directly read from a storage medium such as a memory card or the
like. Or the functions include a function of printing image data
received from a digital camera or the like.
[0046] To implement these functions, the MFP 100 comprises a
scanning device 134 such as a flatbed scanner or the like, and a
printing device 133 of an ink-jet system, electrophotography
system, or the like. Also, the MFP 100 comprises a display panel
139 used to notify the user of various states, and an operation
panel 135 including various key switches, and the like, which are
used to accept various instructions from the user. The MFP 100
comprises a USB port (not shown) used to communicate with the PC on
its back surface, and the USB port allows the MFP 100 to make
various communications with the PC. In addition to the above
arrangement, the MFP 100 comprises a card slot 142 used to read out
data from various memory cards, and a camera port 143 used to make
direct communications with a digital still camera (DSC). In
addition, the MFP 100 comprises an auto document feeder (to be
abbreviated as ADF hereinafter) 131 used to automatically set a
document on a document table.
[0047] FIG. 2 is a block diagram showing the internal arrangement
of the MFP 100.
[0048] A CPU 211 controls various functions of the MFP 100 by
executing various image processing programs stored in a ROM 216 in
accordance with operations accepted from the user at an operation
unit 215.
[0049] A scanning unit 214 corresponds to the scanning device 134,
scans a document image using an optical sensor such as a CCD or the
like, and outputs analog brightness data of, for example, red (R),
green (G), and blue (B). The scanning unit 214 may comprise a
contact image sensor (CIS) in place of the CCD. Using the
aforementioned ADF 131, the scanning unit 214 can successively scan
order sheets and the like.
[0050] A card interface 222 corresponds to the card slot 142, and
reads image data, which is captured by, for example, a DSC and is
stored in a memory card or the like, in accordance with an
operation by the user at the operation unit 215. Note that the
color space of image data read via the card interface 222 is
converted from that (e.g., YCbCr) of the DSC into a standard RGB
color space (e.g., NTSC-RGB or sRGB) if necessary. The read image
data undergoes processes such as resolution conversion into the
effective number of pixels and the like based on its header
information as needed. A camera interface 223 corresponds to the
camera port 143, and reads image data by directly connecting a
DSC.
[0051] An image processor 212 is a functional unit for applying
image processes to be described later to image data. For example,
the image processor 212 executes image processes such as image
analysis, calculations of conversion characteristics, conversion
from brightness signals (RGB) into density signals (CMYK), scaling,
gamma conversion, error diffusion, and the like. The image data
that has undergone these image processes is stored in a RAM 217.
When data stored in the RAM 217 reaches a predetermined data size
required to be printed by a printing unit 213 corresponding to the
printing device 133, the printing unit 213 executes a print
operation.
[0052] A nonvolatile RAM 218 comprises, for example, a battery
backed-up SRAM or the like, and stores data unique to the image
processing apparatus or the like.
[0053] The operation unit 215 corresponds to the operation panel
135, and is a functional unit that accepts various operations from
the user. For example, the operation unit 215 comprises keys
specialized to attain specific processes such as a photo direct
print start key which allows the user to select image data stored
in a storage medium (memory card) and to start printing, a key used
to print an order sheet, a key used to scan an order sheet, and the
like. The operation unit 215 also comprises a copy start key in a
monochrome copy mode or color copy mode, a mode key used to
designate a mode such as a copy resolution, image quality, and the
like, a stop key used to stop a copy operation or the like.
Furthermore, the operation unit 215 comprises a numerical keypad
used to input a copy count, a registration key, and the like. The
CPU 211 detects the pressing states of these keys and controls
respective units according to the detected states.
[0054] A display unit 219 corresponds to the display panel 139,
comprises a dot matrix type liquid crystal display unit (LCD) and
an LCD driver, and makes various displays under the control of the
CPU 211. Also, the display unit 219 may display thumbnails of image
data recorded on a storage medium.
[0055] The printing unit 213 corresponds to the printing device
133, and comprises an ink-jet head of an ink-jet system,
general-purpose IC, and the like. The printing unit 213 reads out
image data stored in the RAM 217 and prints it out as a hard copy
under the control of the CPU 211.
[0056] A drive unit 221 includes stepping motors for driving feed
and discharge rollers, gears for transmitting the driving forces of
the stepping motors, a driver circuit for controlling the stepping
motors, and the like in the operations of the scanning unit 214 and
printing unit 213.
[0057] A sensor unit 220 includes a print sheet width sensor, print
sheet sensor, document width sensor, document sensor, print medium
sensor, and the like. The CPU 211 detects the states of a document
and print sheet based on information obtained from this sensor unit
220.
[0058] A PC interface 224 is an interface between the PC and MFP
100. The MFP 100 can accept a print operation, scan operation, and
the like from the PC via the PC interface 224.
[0059] In a copy operation by the MFP 100 alone, the image
processor 212 processes image data, which is scanned by the
scanning unit 214 based on the user's operation at the operation
unit 215, and the printing unit 213 prints the processed image
data.
<Overview of Image Processes>
[0060] FIG. 3 is a flowchart of the processes executed by the image
processor of the MFP. Respective steps will be described below, but
a detailed description of the processes will not be given. Note
that the following steps are implemented when the CPU 211 executes
various control programs.
[0061] In step S301, the CPU 211 executes shading correction. That
is, the CPU 211 applies processing for correcting variations of an
image sensing element to image data, which is scanned by the
scanning unit 214 and is A/D-converted.
[0062] In step S302, the CPU 211 executes input device color
conversion. This processing converts image data expressed by an
input device-dependent color space into a standard color space. The
standard color space includes sRGB standardized by IEC
(International Electrotechnical Commission), AdobeRGB propounded by
Adobe Systems, and the like. The conversion method includes an
arithmetic method using a 3.times.3 or 3.times.9 matrix, a lookup
table method which determines values based on a table that
describes conversion rules, and the like.
[0063] In step S303, the CPU 211 executes image
correction/modification processing. More specifically, the image
correction/modification processing includes edge emphasis
processing that corrects blurring as a result of scanning, text
modification processing that improves legibility of text,
processing for removing bleed-through that has occurred due to
scanning upon light irradiation, and the like. Note that details of
the edge emphasis processing will be described later.
[0064] In step S304, the CPU 211 executes enlargement/reduction
processing. This processing converts image data to a desired scale
when the user designates a zoom scale, a 2-in-1 copy mode that lays
out two document images on one sheet, or the like. As the
conversion method, methods such as bicubic, nearest neighbor, and
the like are generally used.
[0065] In step S305, the CPU 211 executes output device color
conversion. This processing converts image data expressed by the
standard color space into that data expressed by an output
device-dependent color space. For example, when the printing unit
213 of the MFP 100 of this embodiment adopts an ink-jet system that
uses inks of cyan (C), magenta (M), yellow (Y), black (K), and the
like, RGB data is converted into CMYK data. This conversion
processing is the same as that in step S302.
[0066] In step S306, the CPU 211 executes quantization processing
of image data. That is, the CPU 211 converts image data into tone
levels that can be printed by the printing unit 213. For example,
in the case of binary expression, that is, ON/OFF of ink dots in
the ink-jet printing unit, image data may be binarized by a
quantization method such as error diffusion or the like. As a
result, the quantization processing can convert image data into a
data format that the printing unit 213 can process, and the
printing unit 213 executes a print operation based on this image
data.
<Image Processing Unit>
[0067] FIG. 4 is a view for explaining a processing unit of the
image processes upon execution of the image processes.
[0068] A case will be explained below wherein the processing unit
is a pixel unit. Assuming that a pixel indicated by ".largecircle."
in an upper view of FIG. 4 is a pixel of interest (pixel to be
processed), a region (7.times.7 region) defined by 7.times.7 pixels
including the pixel of interest is set, as indicated by the bold
line in the upper view of FIG. 4. A correction intensity for the
pixel of interest is set using the image data in the 7.times.7
region set in this way, thus correcting the pixel of interest.
After correction of the pixel of interest, a pixel that neighbors
the pixel of interest is set as the next pixel of interest, as
indicated by ".times." in, for example, a middle view of FIG. 4,
and a 7.times.7 region is set to have the pixel indicated by
".times." as the pixel of interest, so as to similarly execute the
correction processing. After that, the pixel of interest is
similarly shifted pixel by pixel in turn and a new 7.times.7 region
is set in each case, thus correcting all pixels to be
corrected.
[0069] A case will be explained below wherein the processing unit
is a region unit. A 7.times.7 region is set for a pixel indicated
by ".largecircle." in the upper view of FIG. 4, and a correction
intensity to be set for ".largecircle." is applied to a plurality
of pixels, for example, all pixels, in the 7.times.7 region. As the
next processing unit, a 7.times.7 region is set for a pixel
indicated by ".DELTA." in a lower view of FIG. 4. In this way, the
processing unit is shifted, so that the 7.times.7 region for
".largecircle." neighbors that for ".DELTA.". However, the pixel
unit is preferably used as the processing unit to set the
correction intensity at higher accuracy. In the embodiments to be
described hereinafter, the pixel unit will be described as the
processing unit.
[0070] FIG. 5 is a flowchart for explaining the operation for
shifting the processing unit.
[0071] Step S501 is setting processing of a processing target
(pixel to be processed). After the start of the processing, the CPU
211 sets a first pixel to be processed. If the process returns from
step S505 to step S501, the CPU 211 sets the next pixel to be
processed.
[0072] In step S502, the CPU 211 sets a processing region. The
processing region is a region configured by a plurality of pixels
(7.times.7 region) including the processing unit, as described
above.
[0073] In step S503, the CPU 211 sets a correction intensity. That
is, the CPU 211 sets a correction intensity for the processing
unit. In step S504, the CPU 211 corrects the processing unit using
the correction intensity set in step S503.
[0074] The CPU 211 determines the last correction target in step
S505, that is, checks if the processed processing unit is the last
one. If the processing unit is not the last one (NO), the process
returns to step S501. If the processing unit is the last one (YES),
this processing ends.
[0075] In replacement processing of this embodiment, the 7.times.7
region will be described as the processing region. This is because
the pixel range of a document to be scanned by one pixel of the
image sensing element (CCD or CIS) used in the scanning device 134
described using FIG. 1 and the scanning unit 214 described using
FIG. 2 is designed to include six pixels or less. Although the
pixel range to be scanned is designed to include six pixels or
less, reflected light from a document that enters the image sensing
element receives various influences due to float of a document from
the document table, unevenness of a document, and the like. For
this reason, one pixel of the image sensing element may scan a
range exceeding six pixels. The embodiments to be described
hereinafter show a plurality of graphs used to explain image
signals obtained by scanning a document. However, these image
signals are not always obtained from reflected light within six
pixels or less.
[0076] FIGS. 6A and 6B illustrate the range of reflected light that
comes from a document and enters one pixel of the image sensing
element. As shown in FIG. 6A, the image sensing element used in
this embodiment is designed so that reflected light within six
pixels from a 7-pixel range of a document enters one pixel of the
image sensing element (as described above, reflected light that
exceeds six pixels may enter in some cases). That is, reflected
light from one pixel on a document influences seven pixels of the
image sensing element. This causes edge blurring described in the
paragraphs of the related art, and deteriorates sharpness.
[0077] Therefore, upon execution of the edge emphasis processing
based on pixel value replacement, by selecting a replacement
candidate from a pixel region less influenced by a document pixel
corresponding to the pixel of interest, the edge emphasis effect
can be enhanced. For this reason, in order to ensure a minimal
region which is influenced by one pixel of a document image as the
processing region, the 7.times.7 region is set as the processing
region. However, in order to enhance the edge emphasis effect more,
it is effective to set a region exceeding 7.times.7 pixels as a
reference region. Also, when one pixel of the image sensing element
is designed to receive reflected light from a 3-pixel range of a
document, as shown in FIG. 6B, the processing region may be set as
small as a 3.times.3 region. In this manner, the reference region
can be set as needed in accordance with the performance of the
image sensing element such as the number of pixels of the image
sensing element influenced by one pixel of a document image, the
spot size, the number of blurred pixels, Modulation Transfer
Function (MTF), and the like.
[0078] Definitions and limitations of terms used in the description
of the embodiments of the present invention will be described
below.
[0079] In the embodiment to be described below, a fluctuation count
will be described as the number of sign changes (the number of
zero-crossing points) in brightness changes in a region of
interest. However, the present invention is not limited to such
specific definition. That is, the fluctuation count is defined as a
value that expresses the frequency of occurrence of changes in
value associated with image signals such as the number of
zero-crossing points or spatial frequency of the first derivatives
of values associated with image signals in the region of interest,
the number of black-white changes after binarization, and the
like.
[0080] In the embodiment to be described below, a fluctuation
amount will be described as the absolute value (edge amount) of the
brightness difference with respect to a pixel of interest. However,
the present invention is not limited to such specific definition.
That is, the fluctuation amount is defined as a value that
expresses the difference (magnitude) of changes such as the
absolute value of the first derivative of a value related to an
image signal of a pixel of interest or the like. Alternatively, the
fluctuation amount is defined as a value that representatively
expresses the difference (magnitude) of changes of values related
to image signals in a region of interest.
[0081] In the embodiment to be described below, a fluctuation
acceleration will be described as a value obtained by further
calculating a difference from the differences of brightness values
in the region of interest. However, the present invention is not
limited to such specific definition. That is, the fluctuation
acceleration is defined as a value that expresses the acceleration
of changes such as the second derivative of values associated with
image signals in the region of interest and the like.
[0082] In the embodiment to be described below, a saturation will
be explained as a maximum absolute value of image signal
differences of respective colors of a pixel or region of interest.
However, the present invention is not limited to such specific
definition. The saturation is defined as a value that expresses the
distance from the brightness axis.
[0083] As will be described in the embodiment to be described
below, adaptive setting of a correction intensity is defined such
that different correction intensities are set for each value in at
least some value regions of those which the defined fluctuation
count, fluctuation amount, fluctuation acceleration, and saturation
can assume.
[0084] Details of the embodiment will be described below. Note that
in the embodiment, an image signal is expressed by RGB components,
and each component is expressed as an 8-bit integer value (0 to 255
in decimal). However, the range of the image signal is not limited
to such a specific range, and may be set to fit the image
processes. Note that white is expressed as R=G=B=255, and black is
expressed as R=G=B=0.
<Details of Edge Processing Operation>
[0085] In this embodiment, the correction intensity set in step
S503 above is an edge intensity, and execution of correction in
step S504 is edge emphasis processing which replaces a pixel by a
predetermined pixel value in a replacement pixel reference region,
which is calculated from the correction intensity. Note that a
replacement pixel reference range to be described later is
adaptively set based on the fluctuation count and edge amount. That
is, a pixel position to be replaced is determined from the
replacement pixel reference range, and a pixel component (pixel of
interest) at an input pixel position is replaced by that at a pixel
position to be replaced.
[0086] FIG. 7 is a detailed flowchart of the edge processing
operation.
[0087] In step S701, the CPU 211 sets a processing region, that is,
a 7.times.7 region including seven pixels in the horizontal
direction and seven pixels in the vertical direction to have the
pixel of interest as the center in an image configured by RGB
multi-valued image signals. Furthermore, the CPU 211 generates a
7.times.7 processing region of brightness L by calculating
brightness L from respective pixel values of the processing region
by:
L=(R+2.times.G+B)/4 (2)
Note that this embodiment uses brightness L given by equation (2),
but may adapt other brightness values derived using other
equations. For example, L* of a uniform color space L*a*b* may be
used as brightness, or a value Y of a YCbCr color space may be used
as brightness.
[0088] FIGS. 8A and 8B illustrate changes in brightness value (L),
first derivative equivalent amount (Grd), and second derivative
equivalent amount (Lap) corresponding to pixel positions for two
types of patterns having different features. An upper graph of FIG.
8 shows a change in brightness value. FIG. 8A shows a change in
brightness value corresponding to pixel positions upon scanning a
black vertical line on a white background in the horizontal
direction. On the other hand, FIG. 8B shows a change in brightness
value corresponding to pixel positions upon scanning halftone dots,
that line up in the horizontal direction on a white background, in
the horizontal direction.
[0089] In step S702, the CPU 211 extracts, from the processing
region of L generated in step S701, pixel values from pixel
sequences in at least two directions. For example, the CPU 211
extracts pixel values of seven pixels in each of a total of four
directions, that is, one horizontal direction 901, one vertical
direction 902, and two oblique directions 903 and 904, as shown in
FIG. 9.
[0090] In step S703, the CPU 211 calculates differences Grd
corresponding to first derivatives of L of five pixels in each
direction from L in the four directions extracted in step S702, as
shown in FIG. 10, and using:
Grd(i)=L(i+1)-L(i-1) (3)
where L(i-1) is a pixel before pixel L(i), and L(i+1) is a pixel
after pixel L(i).
[0091] Note that the difference between two pixels before and after
the pixel of interest is calculated so that the derived Grd value
corresponds to each pixel position. However, other methods may be
used. For example, differences between neighboring pixels may be
calculated, or differences between pixels further separated from
those before and after a given pixel described above may be
calculated. In this case, interpolation processing or the like may
be used together, so that the pixel position matches that where the
Grd value is derived.
[0092] Middle graphs of FIGS. 8A and 8B show changes in Grd value
calculated by applying equation (3) to the brightness values L in
the upper graphs.
[0093] In step S704, the CPU 211 calculates Grd absolute values in
the four directions at the position of the pixel of interest in Grd
in the four directions calculated in step S703 and determines an
edge direction. More specifically, the CPU 211 determines a
direction that shows a maximum Grd absolute value of those in the
four directions as an edge direction of the pixel of interest.
[0094] In step S705, the CPU 211 derives, as an edge amount, a
maximum absolute value from five pixels of Grd of the edge
direction calculated in step S703 in the edge direction determined
in step S704. That is, an edge is stronger with increasing edge
amount, and is close to flat with decreasing edge amount.
[0095] In step S706, the CPU 211 calculates a fluctuation count as
a total of the four directions from the Grd values in the four
directions calculated in step S703.
[0096] FIG. 11 shows graphs for explaining a fluctuation count. The
fluctuation count is the number of times the sign of Grd changes
from + to - or vice versa, as shown in a graph 1101. Alternatively
the fluctuation count (the number of zero-crossing points) of the
pixel of interest is obtained by calculating the number of times
the sign of Grd changes from + to 0 and then to - at the next
pixel, or from - to 0 and then to + at the next pixel, as shown in
a graph 1102. That is, the number of times of changes shown in each
of the graphs 1101 and 1102 is counted as twice.
[0097] Note that this embodiment does not count, as the fluctuation
count, a case in which the sign changes to sandwich zeros of a
plurality of pixels, as shown in a graph 1103, or a case in which
the Grd value becomes zero but its sign does not change, as shown
in a graph 1104. When the Grd values assume zero at the plurality
of pixels or when the Grd values become zero but their sign does
not change, a bold line is likely to be determined. As will be
described in step S708, however, an intensity different from that
for a thin line in the graph 1101 or 1102 can be set for the bold
line.
[0098] FIG. 12 shows graphs for explaining an edge threshold and
smoothing threshold. As shown in FIGS. 8A and 8B, text tends to
have a smaller fluctuation count than halftone. However, depending
on the density uniformity of a document or shading accuracy, text
often has changes with small amplitudes in Grd, as shown in a graph
1201. In such case, the fluctuation count increases like halftone,
and if correction intensity setting processing (to be described
later) is executed, an edge intensity close to that of halftone is
undesirably set. Hence, when the edge amount calculated in step
S705 is relatively large, that is, when it exceeds a set threshold,
small Grd values are smoothed to zero to set an edge intensity with
higher accuracy. More specifically, the edge amount calculated in
step S705 is compared with a threshold (edge threshold), and if the
edge amount exceeds the edge threshold, a smoothing threshold is
set, as shown in a graph 1202. In case of Grd absolute values equal
to or smaller than the smoothing threshold, the fluctuation count
is counted to have Grd=0, as shown in a graph 1203. In this manner,
the fluctuation count of text can be suppressed, and the edge
intensity setting processing with high accuracy can be
attained.
[0099] In step S707, the CPU 211 adaptively sets an edge intensity
Fz in accordance with the fluctuation count calculated in step
S706. A graph 1301 in FIG. 13 is used to explain the Fz setting in
step S707: the abscissa plots the fluctuation count, and the
ordinate plots Fz. In case of the fluctuation count which is
smaller than a first threshold and with which a text region is more
likely to be determined, Fz is set to be 1 to emphasize the edge.
In case of the fluctuation count which is larger than a second
threshold and with which a halftone region that readily causes
moire at high LPI is more likely to be determined, Fz is set to be
0 so as not to emphasize moire. In case of the fluctuation count
falling within a range between the first and second thresholds
(both inclusive), Fz is adaptively set for each fluctuation count
to obscure switching of the processes. More specifically, the CPU
211 can adaptively set Fz using equation (4) below corresponding to
the graph 1301:
Fz=(second threshold-fluctuation count)/(second threshold-first
threshold) (4)
Note that when the fluctuation count=first threshold, Fz=1; when
the fluctuation count=second threshold, Fz=0.
[0100] In step S708, the CPU 211 adaptively sets an edge intensity
Fe in accordance with the edge amount calculated in step S705. A
graph 1302 in FIG. 13 is used to explain the Fe setting in step
S708: the abscissa plots the edge amount, and the ordinate plots
Fe. In case of the fluctuation amount which is smaller than a third
threshold and with which a flat region is more likely to be
determined, Fe=0 is set so as not to roughen an image by
emphasizing small fluctuation amounts. In case of the fluctuation
amount which is larger than a fourth threshold and with which an
edge region is more likely to be determined, Fe=1 is set to apply
edge emphasis. In case of the fluctuation amount falling within a
range between the third and fourth thresholds (both inclusive),
different Fe is adaptively set for each edge amount, so as to
obscure switching of the processes. More specifically, the CPU 211
can adaptively set Fe using equation (5) below corresponding to the
graph 1302:
Fe=(edge amount-third threshold)/(fourth threshold-third threshold)
(5)
[0101] Note that when the edge amount-third threshold, Fe=0; when
the edge amount=fourth threshold, Fe=1.
[0102] In step S709, the CPU 211 calculates a replacement pixel
reference range based on the edge intensity using Fz calculated in
step S707 and Fe calculated in step S708. Since this embodiment
adopts 7.times.7 pixels as the processing unit, as described above,
a maximum reference range is defined by 7 pixels, and the reference
range is determined based on the Fz and Fe values. A calculation
method of the replacement pixel reference range is given by:
Replacement pixel reference range=maximum reference
range.times.Fz.times.Fe (6)
[0103] Since the ranges of the Fz and Fe values are set to meet
0.ltoreq.Fz.ltoreq.1 and 0.ltoreq.Fe.ltoreq.1, the reference range
is defined by the value obtained by multiplying the maximum
reference range by Fz and Fe.
[0104] In order to match the reference range from the central pixel
to the pixel positions, the replacement pixel reference range may
be adjusted to be defined by an odd number of pixels. For example,
since this embodiment defines the processing region by 7.times.7
pixels, a value that can be assumed is 7, 5, 3, or 1. More
specifically, when the value of the replacement pixel reference
range calculated using equation (6) meets one of the following
inequalities, the replacement pixel reference range can be defined
by an odd number of pixels as follows:
[0105] when 0.ltoreq.replacement pixel reference range<2,
replacement pixel reference range is set to be "1";
[0106] when 2.ltoreq.replacement pixel reference range<4,
replacement pixel reference range is set to be "3";
[0107] when 4.ltoreq.replacement pixel reference range<6,
replacement pixel reference range is set to be "5"; or
[0108] when 6.ltoreq.replacement pixel reference range.ltoreq.7,
replacement pixel reference range is set to be "7".
[0109] In step S710, the CPU 211 extracts a pixel sequence in the
edge direction determined in step S704 from those in the four
directions extracted in step S702. The CPU 211 extracts the
replacement pixel reference range calculated in step S709 to have
the pixel of interest as the center, and determines pixel positions
with maximum L and minimum L within that range.
[0110] FIG. 15 is a graph for explaining the derivation sequence of
the pixel positions with maximum L and minimum L when the
replacement pixel reference range is defined by five pixels. In
FIG. 15, a black dot 1501 represents the central pixel, and gray
dots 1502 to 1505 represent pixels within the replacement pixel
reference range. Since the replacement pixel reference range is
defined by five pixels, pixels that can be replacement candidates
are those at positions of .+-.2 pixels from the center, and the
pixel positions with maximum L and minimum L are calculated from
these five pixels. In FIG. 15, maximum L corresponds to the pixel
position of the gray dot 1505, and minimum L corresponds to that of
gray dot 1502.
[0111] When the value calculated in step S709 is not limited to an
odd value, values located at .+-.(replacement pixel reference range
-1)/2 from the central pixel are calculated from two neighboring
pixels by interpolation. That is, the outermost positions of the
replacement pixel reference range assume pixel values calculated by
interpolation, and the remaining positions assume pixel values
according to the pixel positions. FIG. 16 is a graph for explaining
the derivation sequence of pixel positions with maximum L and
minimum L when the replacement pixel reference range is defined by
six pixels. In FIG. 16, a black dot 1601 represents the central
pixel, and gray dots 1603 to 1606 and white squares 1608 and 1609
represent pixels within the replacement pixel reference range. Note
that the white square 1608 represents a pixel obtained from the
gray dots 1602 and 1603 by interpolation, and the white square 1609
represents a pixel obtained from the gray dots 1606 and 1607 by
interpolation. Since the replacement pixel reference range is
defined by six pixels, pixels which can be replacement candidates
are those up to the positions of .+-.2.5 pixels from the center.
For this reason, the white squares 1608 and 1609 as outermost
pixels are calculated by interpolating two neighboring pixels, as
described above, and the pixel positions with maximum L and minimum
L are calculated from these seven pixels. In FIG. 16, maximum L
corresponds to the pixel position of the white square 1609, and
minimum L corresponds to that of white square 1608.
[0112] In step S711, the CPU 211 calculates a fluctuation
acceleration Lap as the second derivative of three pixels from Grd
of the edge direction calculated in step S703 in the edge direction
determined in step S704. The calculation method of the fluctuation
acceleration is described by:
Lap(i)=Grd(i+1)-Grd(i-1) (7)
where Grd(i-1) is a pixel before pixel Grd(i), and Grd(i+1) is a
pixel after that pixel. Note that the calculation method of the
fluctuation acceleration is not limited to such specific equation,
and the difference between neighbor Grd values may be
calculated.
[0113] Lower graphs of FIGS. 8A and 8B respectively show changes in
Lap values calculated by applying equation (7) to Grd shown in the
upper graphs.
[0114] In step S712, the CPU 211 determines a replacement pixel
position based on the pixel positions with maximum L and minimum L
determined in step S710 and the fluctuation accelerations Lap
calculated in step S711.
[0115] FIG. 19 is a table for explaining the determination method
of the replacement pixel position. In FIG. 8A or 8B, when the sign
of Lap is +, L of the pixel of interest tends to assume a value,
the magnitude of which is closer to minimum L than maximum L; when
the sign of Lap is -, L of the pixel of interest tends to assume a
value, the magnitude of which is closer to maximum L than minimum
L. Hence, in this embodiment, the replacement pixel position is
determined, as shown in FIG. 19. Note that handling of the edge
center where Lap of the pixel of interest becomes zero is not
limited to FIG. 19. When Lap of the pixel of interest is zero, the
pixel position with maximum L or minimum L may be determined as the
replacement pixel position.
[0116] In step S713, the CPU 211 calculates a replacement level
using the pixel value of the replacement pixel position determined
in step S712. That is, the CPU 211 extracts RGB values of the
replacement pixel position determined in step S712 from the RGB
7.times.7 regions set in step S701. If the determination result in
step S712 indicates a position between actual pixels, RGB values
are calculated from neighbor pixels by interpolation.
[0117] In step S714, the CPU 211 replaces the RGB values of the
pixel of interest by those calculated in step S713.
[0118] Since the image data is processed via the aforementioned
steps, an image edge part is emphasized.
[0119] FIG. 17 shows graphs illustrating the edge emphasis results
when the replacement pixel reference range is changed for an
identical image. In FIG. 17, white dots represent an original
image, and black dots represent edge modification processing
results.
[0120] A graph 1701 shows a change in brightness value L of the
original image: the ordinate plots L values, the abscissa plots
pixel positions, and white dots represent L values corresponding to
respective pixel positions. A graph 1702 represents the edge
modification processing result when the replacement pixel reference
range is defined by seven pixels. A graph 1704 represents the edge
modification processing result when the replacement pixel reference
range is defined by three pixels. A graph 1703 represents the edge
modification processing result when the replacement pixel reference
range is defined by five pixels.
[0121] When the processing region (block) of the original image
includes a character image or line image, the value of equation (6)
above tends to be large; when the processing region (block)
includes a natural image, that value tends to be small. That is,
the graph 1702 indicates that when the processing region (block)
includes a character image or line image, an image whose range with
tonality decreases, and which is close to a binary image is
obtained. On the other hand, as can be seen from the graph 1704,
when the block includes a natural image, an image whose edge is
emphasized while leaving the tonality of the original image is
obtained. That is, FIG. 17 explicitly shows the effect of changing
the replacement pixel reference range according to an image within
the block as a characteristic feature of the present invention.
[0122] FIG. 18 shows graphs illustrating the edge emphasis results
when the replacement pixel reference range which is set to be
defined by an even number of pixels is changed for an identical
image. A graph 1801 represents an original image as in the graph
1701. A graph 1802 represents the edge modification processing
result when the replacement pixel reference range is defined by six
pixels. A graph 1804 represents the edge modification processing
result when the replacement pixel reference range is defined by two
pixels. A graph 1803 represents the edge modification processing
result when the replacement pixel reference range is defined by
four pixels. FIG. 18 is different from FIG. 17 in that the
replacement pixel reference range does not match the pixel
positions on the original image. However, as can be seen from FIG.
18, an image whose edge is emphasized while leaving the tonality of
the original image as the replacement pixel reference range becomes
smaller is obtained.
[0123] When the replacement pixel reference range does not match
actual pixel positions, as shown in FIG. 18, maximum L and minimum
L can be calculated by generating virtual pixels as the outermost
pixel positions obtained by interpolation using neighbor pixels.
With this method, detailed control can be made independently of the
number of reference pixels, and satisfactory edge modification can
be applied in correspondence with the image type. In FIG. 18, the
replacement pixel reference range is defined by integer values,
that is, 2, 4, and 6 for the sake of descriptive convenience.
However, since the outermost pixel positions are calculated by
interpolation using neighbor pixels, the replacement pixel
reference range may be expressed by decimal values.
[0124] As described above, in the MFP according to the first
embodiment, the edge emphasis technique that can eliminate image
deterioration of a digital image can be provided. Since the edge
intensity is determined based on the fluctuation count and edge
amount in a block, edge emphasis of a halftone region can be
eliminated. Since edge processing based on pixel replacement is
adopted, a reduction of overshoot and undershoot at an edge part
can be attained. In this manner, a high-resolution, multi-gradation
output apparatus can output a high-quality image free from any
bordering.
(Modification)
[0125] In the first embodiment, the edge intensities are determined
based on the fluctuation count and edge amount in a block in steps
5707 and 5708. However, the method of setting the edge intensities
is not limited to such specific method.
[0126] For example, the type of a document image may be accepted
from the user using a user interface (UI). At this time, the type
for the overall document image may be accepted, or the types of a
plurality of regions obtained by separating an image may be
accepted. By determining the edge intensities for the entire image
or each separated region, and executing processing, the same
effects as in the first embodiment can be obtained.
[0127] The edge intensities may be set based on the type of print
medium output in a copy mode. For example, when a print medium is
plain paper, it is determined that a document to be copied includes
character images or line images, and the edge intensities Fz and Fe
are set to be 1, thus applying strong edge modification processing
to the entire image. On the other hand, when a print medium is
photo paper, it is determined that a document to be copied includes
a natural image, and the edge intensities Fz and Fe are set to be
values close to zero, thus applying weak edge modification
processing to the entire image.
Other Embodiments
[0128] The embodiments of the present invention have been explained
in detail. The present invention may be applied to either a system
constituted by a plurality of devices, or an apparatus consisting
of a single device.
[0129] Note that the present invention is also achieved by directly
or remotely supplying a program that implements the functions of
the aforementioned embodiments to a system or apparatus, and
reading out and executing the supplied program code by a computer
of that system or apparatus. Therefore, the technical scope of the
present invention includes the program code itself installed in a
computer to implement the functional processes of the present
invention using the computer.
[0130] In this case, the form of program is not particularly
limited, and an object code, a program to be executed by an
interpreter, script data to be supplied to an OS, and the like may
be used as long as they have the program function.
[0131] As a recording medium for supplying the program, for
example, a floppy.RTM. disk, hard disk, optical disk (CD, DVD), and
magneto-optical disk, magnetic tape, nonvolatile memory card, ROM,
and the like may be used.
[0132] As another program supply method, the program may be
supplied as follows. That is, a connection is established to a
homepage on the Internet using a browser of a client computer, and
the program itself according to the present invention or a
compressed file that includes an automatic installation function
may be downloaded to a recording medium such as a hard disk or the
like. Also, the program code that forms the program of the present
invention may be segmented into a plurality of files, which may be
downloaded from different homepages. That is, the claims of the
present invention include a WWW server which makes a plurality of
users download a program required to implement the functional
processes of the present invention by the computer.
[0133] A storage medium such as a CD-ROM or the like, which stores
the encrypted program of the present invention, may be delivered to
the users. The user who has cleared a predetermined condition may
be allowed to download key information that decrypts the program
from a homepage via the Internet, and the encrypted program may be
executed using that key information to be installed on a computer,
thus implementing the present invention.
[0134] Moreover, the functions of the aforementioned embodiments
can be implemented not only by executing the readout program by the
computer but also by some or all of actual processes executed by an
OS or the like which runs on a computer based on instructions of
the program.
[0135] In addition, the functions of the aforementioned embodiments
can also be implemented by some or all of actual processes executed
by a CPU equipped on a function expansion board or unit, which is
inserted into or connected to the computer, based on instruction of
the program read out from the recording medium, after the program
is written in a memory equipped on the function expansion board or
unit.
[0136] While the present invention has been described with
reference to exemplary embodiments, it is to be understood that the
invention is not limited to the disclosed exemplary embodiments.
The scope of the following claims is to be accorded the broadest
interpretation so as to encompass all such modifications and
equivalent structures and functions.
* * * * *