U.S. patent application number 14/447201 was filed with the patent office on 2016-02-04 for spectral print control based on specific spectral ranges of colorants.
The applicant listed for this patent is Hewlett-Packard Development Company, L.P.. Invention is credited to Peter J. KLAMMER, Jan MOROVIC, Peter MOROVIC, James William STASIAK.
Application Number | 20160034796 14/447201 |
Document ID | / |
Family ID | 55180383 |
Filed Date | 2016-02-04 |
United States Patent
Application |
20160034796 |
Kind Code |
A1 |
MOROVIC; Peter ; et
al. |
February 4, 2016 |
SPECTRAL PRINT CONTROL BASED ON SPECIFIC SPECTRAL RANGES OF
COLORANTS
Abstract
Certain methods and systems are described that allow the
spectral control of a print output. A plurality of colorants are
used where one or more colorants contain nanoparticles. Each
colorants has a specified spectral range corresponding to the
constituent nanoparticles. To print with these colorants a spectral
separation may be used that maps an input color with associated
spectral information or direct spectral information to print
control data, the print control data having defined values for
depositions with each combination of the colorants. The spectral
separation may be constructed by characterizing a set of spectral
Neugebauer primaries for the plurality of colorants.
Inventors: |
MOROVIC; Peter; (Sant Cugat
del Valles, ES) ; MOROVIC; Jan; (Colchester, GB)
; KLAMMER; Peter J.; (Corvallis, OR) ; STASIAK;
James William; (Lebanon, OR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Hewlett-Packard Development Company, L.P. |
Houston |
TX |
US |
|
|
Family ID: |
55180383 |
Appl. No.: |
14/447201 |
Filed: |
July 30, 2014 |
Current U.S.
Class: |
358/3.09 ;
358/1.9 |
Current CPC
Class: |
G06K 15/027 20130101;
G06K 15/1878 20130101; G06K 2215/0094 20130101; H04N 1/6033
20130101; G06K 15/1881 20130101 |
International
Class: |
G06K 15/02 20060101
G06K015/02 |
Claims
1. A method comprising: mapping an input color with associated
spectral information to print control data using a spectral
separation, the print control data having defined values for
depositions with each combination of a plurality of colorants, each
colorant having a specified spectral range, wherein the print
control data is usable to produce a print output using the
plurality of colorants, and wherein a set of spectral ranges for
the plurality of colorants provide a distribution of at least one
peak emission value and full-width at half-maximum value over a
given spectral range.
2. The method of claim 1, wherein a set of nanoparticles for each
colorant has a defined narrow-band spectral emission with a
specified full-width at half-maximum value within a visible
spectrum and a defined absorption profile outside of the visible
spectrum.
3. The method of claim 1, wherein the plurality of colorants have a
combined spectral range covering a visible spectrum, and each
colorant is additive in terms of a resulting spectral power
distribution.
4. The method of claim 1, wherein the distribution of the set of
spectral ranges for the plurality of colorants is non-uniform.
5. The method of claim 1, wherein the spectral separation is used
to generate a halftone output.
6. A computer-implemented method of generating a spectral mapping
comprising: obtaining spectral characteristics for a plurality of
colorants, each colorant comprising nanoparticles, each colorant
having a specified spectral range, corresponding to its constituent
nanoparticles, each colorant being additive in terms of a resulting
spectral power distribution, characterizing spectral Neugebauer
primaries for the plurality of colorants based on the obtained
spectral characteristics, a spectral Neugebauer primary
representing an available colorant overprint combination, said
characterizing comprising determining output spectra for one or
more colorant-overprint distribution values for a print substrate;
determining, based on the characterized spectral Neugebauer
primaries, a plurality of key nodes that map at least one input
spectral value to a print control vector comprising colorant
distribution values for each of the spectral Neugebauer primaries;
and generating the spectral mapping by interpolating between the
key nodes.
7. The method of claim 6, wherein a set of nanoparticles for each
colorant has a defined narrow-band spectral emission with a
specified full-width at half-maximum value within the visible
spectrum and a defined absorption profile outside of the visible
spectrum.
8. The method of claim 6, wherein characterizing spectral
Neugebauer primaries comprises defining a colorant-limited gamut
based on the spectral characteristics.
9. The method of claim 6, wherein the spectral separation comprises
a look-up-table with a spectral Neugebauer primary area coverage
vector at each node.
10. The method of claim 7, wherein the input spectral value
comprises one of an input reflectance and a normalized spectral
power distribution and the input spectral value is mapped either:
i) directly to the spectral Neugebauer primary area coverage vector
at each node, or ii) indirectly to a data value between nodes using
interpolation between the spectral Neugebauer primary area coverage
vector at one or more nodes proximate to the data value.
11. A system for spectral printing comprising: a print controller
to map an input color with associated spectral information to a
spectral primary area coverage vector using a spectral separation,
wherein the spectral primary area coverage vector defines values
for depositions with each combination of a plurality of colorants,
each colorant having a specified spectral range, wherein the print
controller is to communicate the spectral primary area coverage
vector to a printing device to generate a print output using the
plurality of colorants, and wherein each of the plurality of
colorants includes a set of nanoparticles that has a defined
narrow-band spectral emission with a specified full-width at
half-maximum value within a visible spectrum.
12. The system of claim 11, wherein the set of nanoparticles for
each colorant has a defined absorption profile outside of the
visible spectrum.
13. The system of claim 12, wherein the nanoparticles comprise
quantum dots.
14. The system of claim 11, wherein a set of spectral ranges for
the plurality of colorants provide a non-uniform distribution of
peak emission values within a given spectral range.
15. The system of claim 11, wherein the spectral separation or
print data is used to generate a halftone output.
Description
BACKGROUND
[0001] When printing it is desired that a printed color matches a
color of source content as closely as possible, for example under
any viewing or illumination conditions. Printing commonly uses a
colorimetric approach to visually match the printed color to the
color of source content. Colorimetry approximates human color
perception by representing the color of observed surfaces or
objects under a single set of viewing conditions using tristimulus
values--one for each of the three types of light sensitive cells
(cones) lining the retina at the back of the human eye. One type of
cone cell is sensitive mostly to long wavelengths (L), another to
medium wavelengths (M) and yet another to short wavelengths (S) of
electromagnetic radiation in the visible range (i.e., from
approximately 400 to 700 nm). Mostly for historical reasons,
colorimetry uses a linear transformation of the LMS space, derived
from psychophysical color matching experiments, called XYZ, defined
by the CIE (Commission Internationale de l'Eclairage). The
tristimulus values of X, Y and Z of a colorimetric approach form
the basis of approximately representing all colors seen by a human
visual system, tied to a set of viewing conditions, especially an
illuminant present in the observed scene. Colors are thus
identified based on co-ordinates in this CIE XYZ space.
BRIEF DESCRIPTION OF THE DRAWINGS
[0002] Various features and advantages of the present disclosure
will be apparent from the detailed description which follows, taken
in conjunction with the accompanying drawings, which together
illustrate, by way of example only, features of the present
disclosure, and wherein:
[0003] FIG. 1 is a schematic illustration of a system for spectral
printing according to an example;
[0004] FIG. 2 is a schematic illustration showing a print pipeline
according to an example;
[0005] FIG. 3 is a flowchart showing a method of using a spectral
printing system according to an example;
[0006] FIG. 4 is a flowchart showing a method of generating a
spectral mapping according to an example;
[0007] FIG. 5 is a schematic illustration of a print control vector
according to an example; and
[0008] FIGS. 6A, 6B and 6C are spectra showing the wavelength
ranges for a set of spectral primaries according to an example;
[0009] FIG. 7 is a spectrum showing non-uniform wavelength ranges
for a set of spectral primaries according to an example
[0010] FIG. 8 is a schematic illustration of a processing device
that may be used to implement at least an encoder according to an
example.
DETAILED DESCRIPTION
[0011] In the following description, for purposes of explanation,
numerous specific details of certain examples are set forth.
Reference in the specification to "an example" or similar language
means that a particular feature, structure, or characteristic
described in connection with the example is included in at least
that one example, but not necessarily in other examples.
[0012] Certain examples described herein relate to color mapping in
an imaging system. Color mapping is a process by which a first
representation of a given color is mapped to a second
representation of the same color. Although "color" is a concept
that is understood intuitively by human beings, it can be
represented in a large variety of ways. Color intrinsically relates
both to a physical stimulus as well as to its perception or
interpretation by a human or artificial observer under a given set
of conditions. The physical foundation relates to the spectral
power distributions of the illuminating light source and the
reflective or transmissive properties of an object or surface as
well as the observers' spectral sensitivities. Further elements
affect color, such as temporal or spatial effects. The perception
of color is then the joint effect of all this elements. There are
different ways to describe color, the descriptions differing, for
example, in how limited their validity is. For example, in one case
a surface may be represented by a power or intensity spectrum
across a range of visible wavelengths. This provides information
about a physical property of the surface, but not about the
ultimate color as that also depends on the illuminant and an
observer, spatial context etc. At the other extreme, a surface's
color can be described with all other conditions fixed, e.g. the
tristimulus values of the surface under an average intensity
daylight-simulating illuminant against a gray background, in which
case a Color Appearance Model would be used to describe it. In yet
other cases, a "color" may be defined as a category that is used to
denote similar visual perceptions; two colors are said to be the
same if they produce a similar effect on a group of one or more
people. These categories can then be modelled using a lower number
of variables.
[0013] Within this context, a color model may define a color space.
A color space in this sense may be defined as a multi-dimensional
space, wherein a point in the multi-dimensional space represents a
color value and dimensions of the space represent variables within
the color model. For example, in a Red, Green, Blue (RGB) color
space, an additive color model defines three variables representing
different quantities of red, green and blue light. Other color
spaces include: a Cyan, Magenta, Yellow and Black (CMYK) color
space, wherein four variables are used in a subtractive color model
to represent different quantities of colorant, e.g. for a printing
system; the International Commission on Illumination (CIE) 1931 XYZ
color space, wherein three variables (`X`, `Y` and `Z` or
tristimulus values) are used to model a color, and the CIE 1976
(L*, a*, b*--CIELAB or `LAB`) color space, wherein three variables
represent lightness (`L`) and opposing color dimensions (`a` and
`b`). A spectral space instead may comprise a quantized variable
space representative of a reflectance, emission and/or power
spectrum. This space may have a number of variables representative
of sampled wavelength values or wavelength ranges and one or more
variables representations of one or more of a measured or modelled
reflectance, emission and power value. By itself a spectral space
does not determine color directly, instead it can be projected onto
a variety of color spaces such as a corresponding set of XYZs
colorimetries under additional conditions including an illuminant.
Certain color spaces, such as RGB and CMYK may be said to be
device-dependent, e.g. an output color with a common RGB or CMYK
value may have a different perceived color when input to different
imaging systems.
[0014] When working with color spaces, the term "gamut" refers to a
multi-dimensional volume in a color space that represents color
values that may be output or captured by a given imaging system. A
gamut may take the form of an arbitrary volume in the color space
wherein color values within the volume are available to the imaging
system but where color values falling outside the volume are not
available. A "spectral gamut" is the equivalent volume in a
spectral space. The terms color mapping, color model,
color/spectral space and gamut, as explained above, will be used in
the following description.
[0015] Certain examples described herein provide an ability to
control a print output spectrally rather than colorimetrically,
e.g. based on variables representative of spectral quantities as
opposed to tristimulus values. This allows for colors in print
outputs to match colors in source content under a wide range of
viewing and/or illumination conditions. More generally, it enables
a match at the spectral level, independent of viewing conditions.
To achieve this, certain examples make use of a colorant set that
is capable of reproducing electromagnetic spectra representative of
one or more colors of source content. For example, these spectra
may be measured from a desired color representation, such as from a
display device, photograph, object etc.. Given this colorant set
and an input color with associated spectral information, e.g. an
indication of a desired spectral output, certain examples described
herein can match this input color spectrally.
[0016] In certain cases described herein, a set of colorants are
configured to provide a number of "color channels" that are
characterized in spectral space, e.g. that have specified spectra.
For example, one or more colorants may have suitable properties
based on nanoparticles such as quantum dots. These nanoparticles
may be configured to have a particular emissive spectrum. In
certain case, this spectrum may include narrow-band emissive
regions, e.g. narrow in relation to the full range of visually
perceivable colors. In other cases, the emissive spectrum may be
parameterized by one or more peak emission values and one or more
wavelength ranges.
[0017] In certain cases described herein, an ability to control a
print output spectrally allows for a spectral print pipeline, e.g.
a set of print processing stages from a data file input to a print
output. This spectral print pipeline can make full use of a
pipeline without metamerism and color inconstancy. A spectral
pipeline results in reproductions that match the input spectra as
closely as possible and, assuming a perfect match, cannot be
distinguished from the original, regardless of the conditions
(illuminants, observers) under which they are inspected. This is in
contrast to a colorimetric pipeline where a match is sought under a
single set of conditions, typically in print this is illuminant D50
and the CIE 1931 Standard Colorimetric Observer, since the pipeline
is based on XYZ tristimuli for these conditions. Also, a spectral
pipeline that has access to spectrally narrow-band (sometimes
referred to as `pure`) inks may provide large gamut gains in
comparison to a colorimetric print pipeline using comparative inks
as the spectrally pure primaries are at the boundary of physically
realizable spectra. For example a spectrally pure `red` may have a
single, narrow-band peak emission in its spectrum at around 610 nm
with no other emissions elsewhere. This spectrum is impossible to
achieve on a comparative printing system with typical inks as
combining a Magenta and a Yellow ink which have broad absorptions
and broad emissions across the visible range. In this context a
"spectral primary" comprises a colorant with a particular spectral
profile, e.g. a defined power distribution with
reflectance/emission in one set of ranges, the power distribution
representing, at each wavelength, the proportion of incident
electromagnetic radiation that is respectively reflected, emitted
and absorbed.
[0018] FIG. 1 shows a system 100 for spectral printing according to
an example. The system 100 comprises a print controller 110 and a
printing device 120. The printing device 120 is arranged to use a
plurality of colorants 130 to produce a print output 140 on a
substrate 150. For example, the printing device 120 may comprise an
ink-jet printer with a number of print heads that are arranged to
emit the plurality of colorants. In the example of FIG. 1 there are
seven colorants labelled A to G. The print output 140 comprises
portions of colorant 130 that are deposited onto the substrate 150
by way of the printing device 120. In the example of FIG. 1, an
area of the print output 140 comprises a colorant overprint, in
that a portion of deposited colorant C--145C--and a portion of
deposited colorant F--145F--is overprinted with a portion of
colorant D--145D. The print controller 110 is arranged to generate
print control data from input image data (not shown). The print
control data has defined values for depositions with each
combination of the colorants 130. In certain cases the print
control data may comprise a distribution vector that specifies a
distribution of colorant depositions, e.g. a probability
distribution for each colorant and/or colorant combination for a
pixel of a print image or, in other words, an area coverage vector
for a set of colorant combinations or overprints. The term
"colorant" as used herein refers to any colorant suitable for
printing, including, amongst others a printing fluid, for example
an ink, a gloss, a varnish or a coating, and non-fluid printing
materials, for example a toner, a wax or a powder used in laser
printing or dry electrophotography; any references to "ink" as used
below include a colorant as so defined
[0019] As described in more detail in later examples, one or more
of the colorants 130 comprise additives that configure the spectral
properties of the colorant, e.g. the measured spectra when the
colorant is deposited on the substrate 150. In this example, the
additives comprise nanoparticles. These may be nano-crystals such
as quantum dots. These quantum dots comprise semi-conductor-like
materials that may be configured and manufactured such that they
exhibit narrow-band emission spectra within the visible range and
defined absorption profiles outside of the visible range, e.g. in
the ultra-violet or infra-red range. A colorant may comprise a
quantum dot material component with a concentration of less than 1%
by weight to around a few % by weight. These spectra may have a
controlled peak location and a controlled full width at half
maximum (FWHM). For example, quantum dots of the same material but
different sizes may emit light in different wavelength ranges due
to the quantum confinement effect. For certain materials, the
larger the quantum dot the longer the wavelength of the spectral
peak (e.g. the redder the perceived output); while the smaller the
quantum dot the shorter the wavelength of the spectral peak (e.g.
the bluer the perceived output). Quantum dots may range from 2 to
50 nm in size for certain materials and production techniques. In
certain cases shell size may also be configured to affect the
properties of the quantum dot. Quantum dots may also be configured
to absorb electromagnetic radiation both within as well as outside
of the visible range, for example light in the ultra-violet or
infra-red range. In general, the nanoparticles may have one or more
of up-converting and down-converting properties, i.e. it may absorb
radiation at a given set of wavelengths and re-emit radiation at a
set of wavelengths which is lower or higher than the radiation it
absorbs.
[0020] In certain cases the set of colorants 130 define a set of
spectral color channels or `spectral primaries`, each spectral
channel being centered on a particular peak wavelength and having a
defined FWHM. The number of spectral primaries, and hence in
certain cases the number of colorants, may be configured to
reproduce any spectra measured at N wavelength samples. For
example, if a visible range is said to be between 400 nm to 700 nm
and this range is sampled at 20 nm steps, then N=16 spectral
primaries are required to reproduce the spectra exactly. In one
case, the set of spectral primaries may be arranged to reproduce a
particular set of content; as such the number of spectral primaries
may be chosen to match the requirements of the content. For
example, if a set of content has a predetermined spectral range,
e.g. that is less than the visible range, fewer spectral primaries
may be required to reproduce the content at a given sampling level.
Additionally or alternatively, when modelling a spectral gamut for
a particular printing device it may be that the available gamut
does not span the entire dimensional domain, e.g. all 16 dimensions
in the previous example. In this case, certain primaries in the
group of 16 could be omitted while minimizing the effect on the
available spectral gamut.
[0021] FIG. 2 is a schematic illustration showing an imaging system
200 according to an example. This imaging system 200 may be used to
print an image spectrally. The imaging system 200 comprises a print
pipeline 230 that is arranged to receive data 210 representative of
an image to be printed and to generate a print output 250. In
certain cases, the print pipeline 230 may comprise print controller
110 and printing device 120 of FIG. 1, wherein print output 250 is
print output 150. The print pipeline 230 is arranged to receive
spectral information 220 associated with the image data 210. The
print pipeline 230 uses one or more spectral separations 240 to
convert the image data 210 and the spectral information 220 to
print control data that is used to generate the print output. In
one implementation, the print pipeline 230 may be arranged to
handle input with spectral information and generate a weighted
combination of spectral Neugebauer primaries as an input to a
halftoning process before print.
[0022] In one case the spectral information 220 may comprise
sampled spectral data for one or more pixels of the image to be
printed. For example, in the case above with sample steps of 20 nm,
a pixel may have associated spectral information in the form of a
spectral vector, the vector having sixteen values and each value
representing a measured or desired reflectance, emission and/or
power value at a particular sampled wavelength. In one case, a
reflectance/normalized emission value may be used, e.g. a value
between 0 and 1 (i.e. 0 and 100%). This value expresses the light
that is reflected or emitted at that pixel as a proportion of the
incident radiation.
[0023] In one case the spectral information 220 may not be defined
for all pixels in the image to be printed and/or for all input
color values in the image data 210. For example one or more
specific spectral objectives may be set for the print output 250 to
match. These may comprise a requirement that a colorimetric
reproduction matches source content under a series of illuminants,
having additional a-priori information about the types of spectra
that are desired in the print output. In this case the image data
210 may comprise tristimulus values (e.g. RGB or XYZ based) and the
desired spectra associated with certain tristimulus values may be
defined. This may be the case for desired `spot` colors such as
brand colors or for certain pigments in paintings for which a
colorimetry or contone RGB value is associated may have a defined
spectral output, e.g. in the form of a sampled spectra. In other
cases one or the spectrally-defined objectives may comprise a
requirement for minimum color inconstancy between an input color
and a print output. Another case could define the spectral
objective as minimizing metamerism within the single
reproduction--i.e. choosing spectra such that if they match under
one set of illuminant conditions they also match under another--or
vice-versa, maximizing metamerism whereby the match only holds
under limited conditions and its mismatch is maximized under other
conditions.
[0024] In the example of FIG. 2, a spectral separation 240 provides
a mapping from the image data 210, together with any requirements
set by the spectral information 220, to print control data, e.g.
data that is used by printing device 120 to deposit colorants. In
cases where particular color values in the image data 210 have
associated spectral information 220, such as a defined spectral
output, a spectral separation 240 may map one or more of the color
values and the defined spectral output to print control data
comprising an output value having a probability distribution for
each colorant and/or colorant combination. This may comprise
processing the color data for the image and any associated spectral
information to generate an input spectral vector that is mapped to
a spectral Neugebauer primary area coverage vector (SNPac) for the
defined set of colorants. In this case, a spectral separation 140
may be defined as a look-up table in a spectral domain, with SNPac
vectors as the output in each node of the table. In another case,
image data 210 may be mapped to a vector of colorant percentages or
proportions for each pixel in the print output. In this case, the
colorant percentage vector may be input into a halftoning process
to generate print control data. In the former case where SNPac
vectors are used, at least a portion of the halftoning process may
be integrated into the mapping stage, e.g. as is the case in a
Halftone Area Neugebauer Separation (HANS) system.
[0025] A configuration of the one or more spectral separations 240
may depend on the constraints of any implementing environment. For
example, in a case where there may be size limitations on any used
look-up table, a spectral separation may provide a mapping from a
desired spectral input to print control data for image data
associated with a predefined list of desired spectra while
providing a colorimetric mapping, e.g. from input tristimulus
values or device color coordinates to print control data for image
data that is not associated with a predefined list of desired
spectra. This may be applied for the printing of spot colors where
a spectral fit may be of particularly high value, e.g. tristimulus
or device color image data values associated with these spot colors
may have a spectral mapping whereas tristimulus or device color
image data values not associated with these spot colors have a
mapping from a colorimetric input.
[0026] In another case, a direct spectral look-up table may be
generated with a limited and predetermined set of mapping nodes. In
this case the image data 210 may comprise the spectral information
220, e.g. in the form of a sampled spectral vector for each pixel.
For example, the spectral mapping nodes may be chosen at
approximate colorimetric locations (e.g. skin-tone like
reflectances or other memory-color reflectance areas) known to be
particularly sensitive to perceived color mismatch and/or for
spectra where high accuracy is important. In this case,
N-dimensional simplex interpolation may be used for values between
the nodes, where N is the number of spectral samples used to
represent the image data 210.
[0027] In a further case, image data in a spectral form may be
first converted to a dimensionally-reduced domain such as a LabPQR
color space, where P, Q and R correspond to "metameric blacks".
This may then be mapped to print control data, e.g. to values in a
SNPac space. Alternatively, image data may be received in this
domain and again mapped to a SNPac space.
[0028] FIG. 3 shows a method 300 of configuring a generating a
spectral separation according to an example. This method may be
used to generate one or more of the spectral separations used in
the imaging system of FIG. 2 and/or to configure the print
controller 110 of FIG. 1.
[0029] At block 310, a colorant set is obtained. This may be the
plurality of colorants 130 shown in FIG. 1. To achieve this a set
of narrow-band emission spectra are defined. For example, a desired
number of spectral channels based around a desired set of peak
wavelengths may be defined. These may then be used to determine
and/or develop a set of additives that provide the defined spectra.
For example, a number N of spectral channels may be required in a
range of visible wavelengths (for the human visual system). The
level of spectral control will depend on the number of channels
available whereby spectral channels may be designed to remain as
narrow-band as possible while covering the entire visible range.
The range of visible wavelengths may thus be divided by N and a
FWHM defined such that each spectral channel is discernable. A set
of defined spectral channels where N respectively equals 31, 16 and
7, plus an additional black (B) channel, are shown in FIGS. 6A to
6C. Once each spectral channel is defined the material properties
of a set of photoluminescent materials like quantum dots may be
specified. The design of these materials allows for independent
colorants that correspond 1-to-1 to the spectral channels, e.g.
spectral channel 1 may have a peak at 400 nm with FHWM of 20 nm and
spectral channel 16 a peak at 700 nm with the same FWHM (as shown
in FIG. 6B). A halftone in this domain will therefore have 17
planes (16 spectral primaries plus the black channel). However the
domain of the spectral separation is in a spectral Neugebauer
Primary area coverage domain which allows independent control not
only of the colorants in isolation but also their overprints. Such
treatment of the spectral primaries allows for their independent
use, as is the case in a comparative pipeline as well, however the
spectral primaries or inks being spectral and emissive in this case
means that, coupled with an appropriate pipeline, any conceivable
spectrum can be constructed. Although quantum dots have been used
as an example any material and/or additive that provides
narrow-band spectral emission may be used to define a colorant.
[0030] In this example, the spectral channels or "spectral
primaries" are defined to be additive in terms of the resulting
spectral power distribution. In one implementation they may thus be
printed on a black, i.e. absorptive and spectrally non-selective,
substrate. In another implementation, the narrow-band spectral
emissive primaries may be coupled with a black absorptive ink. In
this implementation, both a black and a gray may be used if the
appearance of a halftone grain is of a particular concern. Use of a
black absorptive ink in this case allows for an efficient and
spectrally-non-selective neutral axis, that when combined with the
spectral primaries is able to extend a gamut into darker areas.
FIGS. 6A to 6C show a case where the respective 31 (plus black), 16
(plus black) and 7 (plus black) spectral primaries are defined
together with an added black absorptive primary. Each spectral
primary is shown with an approximately Gaussian
reflectance/emission profile, while the black profile has a
constant reflectance/emission value across the visible wavelength
range (about 15% in the Figures).
[0031] Returning to FIG. 3, at block 320 a spectral separation is
used to maps an input color with associated spectral information to
print control data. The spectral separation has an output space
that has defined values for depositions with each combination of
the colorants defined in block 310. Hence, the spectral separation
maps from the input color to print control data characterized in
terms of the spectral primaries. An example with further detail on
determining a spectral separation is described with reference to
FIG. 4 below. The spectral separation referenced at block 320 is
usable to produce a print output using the plurality of colorants
obtained at block 310, e.g. may be useable as a spectral separation
240 or as a control configuration for print controller 110.
[0032] FIG. 4 shows a method 400 of generating a spectral mapping
according to an example. This spectral mapping may form part of a
"spectral" separation, e.g. the method 400 may be used to generate
the spectral separation of block 320 of FIG. 3.
[0033] At block 410 of FIG. 4 a set of spectral characteristics are
obtained. Both emissive and absorptive properties may be obtained.
This may be achieved through one or more of measurement and
modelling. In one implementation, an ink template may be used. In
this implementation, an image may be printed with a number of test
patches. The test patches may comprise different distributions of
each of the colorants described previously. For example, each test
patch may be printed based on a different SNPac vector, i.e. with
different proportions of different ink-overprints. The spectral
properties of the test patches may then be measured, e.g. using a
spectrometer or spectrophotometer, which may or may not form part
of the printing system. The test patches may be measured using a
sampling scheme that corresponds to the number of spectral
primaries, e.g. with sampled measurements at N different wavelength
bins. Each measurement may be a reflectance/normalized emission
value. In another implementation, values for spectral properties
may be obtained from an accessible resource, such as a network
and/or storage device.
[0034] At block 420, a set of spectral Neugebauer primaries for the
plurality of colorants are characterized based on the obtained
spectral characteristics. In this case a spectral Neugebauer
primary represents an available colorant overprint combination. The
number of spectral inks (i.e. physical colorants) determines the
number of spectral primaries (the domain of the spectral
separation). If there are N spectral inks covering the visible
range and each ink can be placed at k states (e.g. no ink, one
drop, two drops, etc. to k-1 drops) then there are k.sup.N spectral
Neugebauer primaries. In this case the test patches are printed
across the range of colorants, and the spectral properties of the
print output are analyzed so as to identify the spectral Neugebauer
primaries. An output of block 420 may comprise a set of output
spectra for respective spectral Neugebauer primaries having one or
more colorant-overprint distribution values for a print substrate.
This may take the form of a set of a print control vector
comprising colorant distribution values for each of the spectral
Neugebauer primaries (e.g. SNPacs) and their associated sampled
spectra. In this case a SNPac may be the result of an ink-limited
spectral Neugebauer primary, e.g. a spectral primary overprint that
is limited by the physical capabilities of a given printing
device.
[0035] At block 430, given a set of output spectra for respective
spectral Neugebauer primaries, one or more key nodes of a spectral
mapping such as a look-up table may be defined. This may comprise
defining key nodes for specific desired output spectra, e.g. a
close match between a given spectral output and a given spectral or
colorimetric input may be required for key "spot colors". Output
print control vectors for these nodes are determined first by
interpolation between the print control vectors comprising colorant
distribution values for each of the spectral Neugebauer primaries.
At block 440 a desired resolution of the spectral separation is
determined, e.g. the number of nodes in a look-up table. Color
mappings for these remaining nodes from an input (e.g. either a
spectral or colorimetric) value to a print control vector are then
defined by way of interpolation in the output spectral Neugebauer
primary space between the key nodes and the print control vectors
comprising distribution values for each of the spectral Neugebauer
primaries.
[0036] An example of a print control vector that may form an output
of a spectral separation is schematically illustrated in FIG. 5. As
discussed above, in one case, the print control vector may comprise
colorant overprint statistics to represent a reflectance or
emission spectrum. For example, an output value may comprise a
spectral-primary-overprint area-coverage, i.e. a spectral
Neugebauer primary area coverage or SNPac vector 550. In this case,
the colorant overprint statistics may represent a color halftone
that is printable on an M-level printing device. This may be
compared to a comparative case wherein ink vectors are used as an
output color space. In this comparative case, a color value, e.g.
that represents a pixel or other image portion, may comprise a
continuous tone value, such as a percentage of each of the
available inks in a printing device (e.g. in a CMYK system--[C=20%,
M=30%, Y=0%, K=0%]). In the comparative case, this continuous tone
value may then be input into a separate halftoning system that
applies a particular spatial pattern (a halftone `screen`) and
provides a discrete (e.g. binary in a 2-level printing device)
ink-deposition control output. Colorant overprint statistics, on
the other hand, provide an output that is representative of
different colorant overprint coverages over a virtual unit area
rather than proportions of ink amounts for a pixel. Put in other
words, a SNPac vector may be seen as representing a colorant
overprint probability distribution for a pixel, i.e. the likelihood
that a particular colorant or colorant combination will be printed
at the pixels location. This vector may be used to set specific
pixel values according to these probabilities for a given unit
area.
[0037] As discussed above, a spectral Neugebauer primary may be
defined as a combination of one or more custom colorants (e.g.
inks) in an imaging system, wherein the total set of spectral
primaries represent the total number of colorants combinations that
can be output by the imaging system. A spectral Neugebauer primary
may thus represent one ink, e.g. one of fluids 130, overprinted by
one or more other inks, e.g. another of the fluids 130 in an
addressable area on the substrate 150. For example, if printing
device 120 is a binary (bi-level) printer, a spectral Neugebauer
primary is one of 2.sup.k combinations of k colorants. Other
examples may also incorporate multi-level printers, e.g. where
print heads are able to deposit M drop levels (e.g. M=3 for a
system capable of 0, 1, 2 drop levels). In this case a spectral
primary may comprise one of M.sup.k combinations of k inks. The
term colorant as applied herein applies to, amongst others, inks,
fluids, solids and powders as well as glosses and/or varnishes that
may be deposited in a printing system and that may alter a
perceived output color; these may be modelled as spectral primaries
when additives are used as described herein.
[0038] Returning to FIG. 5, this shows a SNPac vector 550 for an
example case with three spectral primaries: SP1, SP2 and SP3. In
this case there are eight colorant overprint combinations, i.e.
eight spectral Neugebauer primaries: no ink (NI), SP1, SP2, SP3,
SP1+SP2, SP1+SP3, SP2+SP3 and SP1+SP2+SP3. This example shows a
three-by-three pixel area 310 of a print output where all pixels
have the same SNPac vector: vector 550. The vector 550 defines the
probability distributions for each spectral Neugebauer primary for
each pixel. Hence, in the print output there is one pixel of no ink
(335); one pixel of SP1 (305); two pixels of SP2 (315); no pixels
of SP3; two pixels of SP1+SP2 (375); one pixel of SP1+SP3 (345);
one pixel of SP2+SP3 (355); and one pixel of SP1+SP2+SP3 (365). As
can be seen, the component values of each SNPac vector sum to one.
As such, the SNPac vector is representative of the ink overprint
statistics of a given area.
[0039] As described above, certain methods and systems provide an
ability control print spectrally by means of custom-additive
modified colorants. This may provide access to a large gamut due to
the spectrally narrow band spectral channel design. This in turn
contributes to ink-efficiency over comparative color gamuts. For
example, a system with N narrow-band spectral primaries results in
a gamut (under any illuminant) that has vertices which coincide
with the Object Color Solid--the set of all physically possible
surfaces--which is significantly beyond the capability of
comparative printing systems with inks with broad absorptions and
emissions. A large gamut in turn means that over the area of a
typical gamut of a comparative pipeline, even at its extremes,
there is large redundancy in terms of the set of SNPacs that match
a color where a comparative pipeline would have a single candidate
(e.g. a primary at full intensity). Large redundancy in turn
results in the ability to optimize for attributes, such as ink-use.
Hence, a spectral pipeline as described in certain examples, may
allow for better ink-efficiency over the volume of a comparative
pipeline, while also being able to extend its gamut.
[0040] Certain methods and examples may provide advantages over
comparative spectral printing systems that use standard colorants
(e.g. CMYK-based). These comparative systems are limited as the
standard colorants are not designed for spectral printing; for
example, they may be strongly spectrally correlated with each other
as well as each individual ink having strongly correlated
wavelengths, meaning it is impossible to address wavelengths as
such. As a result the spectral performance of such comparative
spectral printing systems, e.g. a measured spectral match with a
defined input spectrum, may be indistinguishable from the spectral
performance of colorimetric data workflows using the same inks.
[0041] A variation of the spectral channels shown in FIGS. 6A to 6C
will now be described with reference to FIG. 7. Although these
spectral channels may also be described as "color channels", as
they may be used to output a color image, they are spectral rather
than colorimetric. In this variation a set of spectral primaries
provide a non-uniform distribution of peak emission values and
wavelength ranges over a visible wavelength range. For example, one
or more of the spacing of peak wavelength values, FWHM values and
emission profile may be non-uniform across a set of spectral
primaries. An example of this variation is shown in FIG. 7 wherein
there is a non-uniform spacing between peak emission values and
FWHM values. FIG. 7 shows eight spectral primaries together with a
black primary, the latter being constant across the visible
range.
[0042] A non-uniform spectral primary selection and representation
has a number of advantages. It allows for encoding efficiency: use
of non-uniform spectral primaries may reduce the size and/or
complexity of any spectral separation (e.g. the size and/or
complexity of the look-up table used to implement the spectral
separation). Using non-uniform variation may help to minimize the
required number of spectral dimensions. Also the human visual
system does not perceive all wavelengths equally due to the
configuration of the cone cells in the retina. Hence, a particular
spectral primary may have a larger FWHM value in a portion of the
visible spectrum where the human visual system is less able to
discriminate between wavelength values, or where it is useful to
have a broad spectrum for efficiency (e.g. the `green` primary
anchored around 540 nm which broadly relates to the Y channel in
XYZ). For example, a configuration for the set of spectral
primaries may be determined by analyzing the types of spectra that
are desired to be reproduced and placing peak emissions at
wavelengths where correlation is low in the target data. In terms
of dimensionality reduction, the variation illustrated in FIG. 7
may be perceived similarly to that of FIGS. 6A or 6B; however the
resulting non-uniform representation is lower dimensional in terms
of the spectral sampling--e.g. in FIG. 7 only eight spectral
samples are needed at the peak wavelength positions: [420, 450,
480, 510, 540, 610, 630, 680], as compared to 31 or 16 samples as
is required with a uniform sampling from 400 to 700 at 10 or 20 nm
steps. The result is an 8-dimensional (D) spectral separation or
look-up table rather than a 16D or 31D separation.
[0043] Certain examples described herein provide both a spectral
means to control a print coupled with inks designed to cover a
large spectral variety (e.g. parametrizeable by the number of inks
available in a system) as well as a significantly bigger
colorimetric gamut than is possible with comparative, absorptive
inks. The examples may be used with both colorimetric and spectral
HANS print pipelines. Although reference is made to a plurality of
colorants in association with described example printing systems,
the plurality of colorants may be used independently and/or
individually.
[0044] Certain methods and systems as described herein may be
implemented by a processor that processes computer program code
that is retrieved from a non-transitory storage medium. FIG. 8
shows an example of an imaging system 800 comprising a
machine-readable storage medium 820 coupled to a processor 810. In
certain case the imaging system 800 may comprise a computer; in
other cases the imaging device may comprise a printer, scanner,
display device, portable computing device or the like.
Machine-readable media 820 can be any media that can contain,
store, or maintain programs and data for use by or in connection
with an instruction execution system. Machine-readable media can
comprise any one of many physical media such as, for example,
electronic, magnetic, optical, electromagnetic, or semiconductor
media. More specific examples of suitable machine-readable media
include, but are not limited to, a hard drive, a random access
memory (RAM), a read-only memory (ROM), an erasable programmable
read-only memory, or a portable disc. In FIG. 8, the
machine-readable storage medium comprises program code to implement
the print controller 850, e.g. that of FIG. 1 of the image
processing apparatus of FIG. 2, or one or more of the methods of
FIGS. 3 and 4. In certain cases, the machine-readable storage
medium may also comprise one or more color mappings 860, which may
be in the form of a spectral separation look-up table.
[0045] The preceding description has been presented to illustrate
and describe examples of the principles described. This description
is not intended to be exhaustive or to limit these principles to
any precise form disclosed. Many modifications and variations are
possible in light of the above teaching.
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