U.S. patent application number 10/831163 was filed with the patent office on 2004-12-30 for lossless region of interest coding.
This patent application is currently assigned to Telefonaktiebolaget LM Ericsson (publ). Invention is credited to Christopoulos, Charilaos, Nister, David.
Application Number | 20040264794 10/831163 |
Document ID | / |
Family ID | 26663099 |
Filed Date | 2004-12-30 |
United States Patent
Application |
20040264794 |
Kind Code |
A1 |
Nister, David ; et
al. |
December 30, 2004 |
Lossless region of interest coding
Abstract
In a method and a device for transmission of S+P transform coded
digitized images a mask is calculated by means of which a region of
interest (ROI) can be transmitted lossless whereby the ROI can be
transmitted and received lossless and still maintaining a good
compression ratio for the image as a whole. This is possible since
no or very few bits can be used for the remaining part of the
image. The calculated mask can also be used for transmitting the
coefficients needed for a lossless region of interest during any
stage of the transmission.
Inventors: |
Nister, David; (Uppsala,
SE) ; Christopoulos, Charilaos; (Sollentuna,
SE) |
Correspondence
Address: |
NIXON & VANDERHYE, PC
1100 N GLEBE ROAD
8TH FLOOR
ARLINGTON
VA
22201-4714
US
|
Assignee: |
Telefonaktiebolaget LM Ericsson
(publ)
Stockholm
SE
|
Family ID: |
26663099 |
Appl. No.: |
10/831163 |
Filed: |
April 26, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10831163 |
Apr 26, 2004 |
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09532768 |
Mar 22, 2000 |
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6775412 |
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09532768 |
Mar 22, 2000 |
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PCT/SE98/01809 |
Oct 7, 1998 |
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Current U.S.
Class: |
382/243 ;
375/E7.049; 375/E7.062; 375/E7.065; 375/E7.141; 375/E7.195;
382/240 |
Current CPC
Class: |
H04N 19/12 20141101;
H04N 19/17 20141101; H04N 19/635 20141101; H04N 19/162 20141101;
H04N 19/115 20141101; H04N 19/146 20141101; H04N 19/127 20141101;
H04N 19/70 20141101; H04N 19/63 20141101; H04N 19/103 20141101 |
Class at
Publication: |
382/243 ;
382/240 |
International
Class: |
G06K 009/36; G06K
009/46 |
Foreign Application Data
Date |
Code |
Application Number |
Oct 10, 1997 |
SE |
9703690-9 |
Jan 16, 1998 |
SE |
9800088-8 |
Claims
1-10. (Canceled).
11. A method of receiving and decompressing an image including at
least one Region of Interest (ROI), comprising: requesting the
image; reading information from a received code stream describing
the ROI in the image; using the information to identify wavelet
transform coefficients needed to reconstruct the ROI; and
transforming the identified wavelet transform coefficients into an
image domain using a wavelet transform to obtain a lossless
reconstruction of the ROI.
12. A method according to claim 11, wherein the image is requested
with a specified ROI instead of reading the ROI's shape and
position from the code stream.
13. A method according to claim 11, further comprising: requesting
a new ROI during or after receiving the image.
14. A method according to claim 11, wherein remaining transform
coefficients are received after the ROI is received.
15. A method according to claim 11, wherein transform coefficients
that do not belong to the ROI are received interleaved with the
transform coefficients that belong to the ROI.
16. A method according to claim 11, wherein the wavelet transform
is an S+P transform.
17. A device for receiving and decompressing an image including at
least one Region of Interest (ROI), comprising electronic circuitry
configured to perform the following tasks: request the image; read
information from a received code stream describing the ROI in the
image; use the information to identify wavelet transform
coefficients needed to reconstruct the ROI; and transform the
identified wavelet transform coefficients into an image domain
using a wavelet transform to obtain a lossless reconstruction of
the ROI.
18. A device according to claim 17, wherein the image is requested
with a specified ROI instead of reading the ROI's shape and
position from the code stream.
19. A device according to claim 17, wherein the electronic
circuitry is further configured to request a new ROI during or
after receiving the image.
20. A device according to claim 17, wherein remaining transform
coefficients are received after the one ROI is received.
21. A device according to claim 17, wherein the transform
coefficients that do not belong to the ROI are received interleaved
with the transform coefficients that belong to the ROI.
22. A device according to claim 17, wherein the wavelet transform
is an S+P transform.
23. A device for receiving and decompressing an image including at
least one Region of Interest (ROI), comprising: means for
requesting the image; means for reading information from a received
code stream describing the ROI in the image; means for using the
information to identify wavelet transform coefficients needed to
reconstruct the ROI; and means for transforming the identified
wavelet transform coefficients into an image domain using a wavelet
transform to obtain a lossless reconstruction of the ROI.
24. A device according to claim 23, wherein the means for
requesting requests the image with a specified ROI instead of
reading the ROI shape and position from the code stream.
25. A device according to claim 23, further comprising: means for
requesting a new ROI during or after receiving the image.
26. A device according to claim 23, wherein remaining transform
coefficients are received after the one ROI is received.
27. A device according to claim 23, wherein the transform
coefficients that do not belong to the ROI are received interleaved
with the transform coefficients that belong to the ROI.
28. A device according to claim 23, wherein the wavelet transform
is an S+P transform.
29. A method for lossless transmission of a region of interest,
comprising: wavelet transforming an image that includes a region of
interest; selecting wavelet transform coefficients from the wavelet
transformed image corresponding to the ROI; calculating an ROI mask
of wavelet transform coefficients using the selected wavelet
transform coefficients; and transmitting the ROI mask to a
receiver, wherein the ROI mask permits the receiver to reconstruct
the ROI losslessly.
30. The method in claim 29, wherein the ROI coefficients are
transmitted before remaining transform coefficients are
transmitted.
31. The method in claim 29, wherein after starting transmission of
the ROI mask, the method further comprising: formulating a new ROI;
selecting new wavelet transform coefficients from the wavelet
transformed image corresponding to the new ROI; calculating a new
ROI mask of wavelet transform coefficients using the new wavelet
transform coefficients; and transmitting the new ROI mask to a
receiver.
32. The method in claim 29, wherein the wavelet transform is an S+P
transform.
33. An apparatus for lossless transmission of a region of interest
(ROI), comprising: means for wavelet transforming an image that
includes a region of interest; means for selecting wavelet
transform coefficients from the wavelet transformed image
corresponding to the ROI; means for calculating an ROI mask of
wavelet transform coefficients using the selected wavelet transform
coefficients; and means for transmitting the ROI mask to a
receiver, wherein the ROI mask permits the receiver to reconstruct
the ROI losslessly.
34. The apparatus in claim 33, wherein the means for transmitting
transmits the ROI coefficients before transmitting remaining
transform coefficients.
35. The apparatus in claim 33, further comprising: means for
formulating a new ROI; means for selecting new wavelet transform
coefficients from the wavelet transformed image corresponding to
the new ROI; means for calculating a new ROI mask of wavelet
transform coefficients using the new wavelet transform
coefficients; and means for transmitting the new ROI mask to a
receiver.
36. The apparatus in claim 33, wherein the wavelet transform is an
S+P transform.
37. An apparatus for lossless transmission of a region of interest
(ROI), comprising electronic circuitry configured to perform the
following tasks: wavelet transform an image that includes a region
of interest; select wavelet transform coefficients from the wavelet
transformed image corresponding to the ROI; calculate an ROI mask
of wavelet transform coefficients using the selected wavelet
transform coefficients; and transmit the ROI mask to a receiver,
wherein the ROI mask permits the receiver to reconstruct the ROI
losslessly.
38. The apparatus in claim 37, wherein the electronic circuitry is
configured to transmit the ROI coefficients before transmitted
remaining transform coefficients.
39. The apparatus in claim 37, wherein the electronic circuitry is
configured to: formulate a new ROI; select new wavelet transform
coefficients from the wavelet transformed image corresponding to
the new ROI; calculate a new ROI mask of wavelet transform
coefficients using the new wavelet transform coefficients; and
transmit the new ROI mask to a receiver.
40. The apparatus in claim 37, wherein the wavelet transform is an
S+P transform.
Description
TECHNICAL FIELD
[0001] The present invention relates to a method and a device for
lossless coding of a region of interest (ROI) in transmission of a
still image. The method and the device are particularly well suited
for the S+P transform.
BACKGROUND OF THE INVENTION AND PRIOR ART
[0002] In transmission of digitized still images from a transmitter
to a receiver, the image is usually coded in order to reduce the
amount of bits required for transmitting the image.
[0003] The reason for reducing the amount of bits is usually that
the capacity of the channel used is limited. A digitized image,
however, consists of a very large number of bits. When transmitting
such an image, consisting of a very large number of bits, over a
channel, which has a limited bandwidth, transmission times for most
applications become unacceptably long, if every bit of the image
has to be transmitted.
[0004] Therefore, much research efforts in recent years have
concerned coding methods and techniques for digitized images,
aiming at reducing the number of bits necessary to transmit.
[0005] These methods can be divided into two groups:
[0006] Lossless methods, i.e. methods exploiting the redundancy in
the image in such a manner that the image can be reconstructed by
the receiver without any loss of information.
[0007] Lossy methods, i.e. methods exploiting the fact that all
bits are not equally important to the receiver, hence the received
image is not identical to the original, but looks, e.g. for the
human eye, sufficiently alike the original image.
[0008] Furthermore, in some applications a part of a transmitted
image may be more interesting than the rest of the image and a
better visual quality of this part of the image is therefore
desired. Such a part is usually termed region of interest (ROI). An
application in which this can be useful is for example medical
databases. In some cases it is also desired or required that the
region of interest is transmitted lossless, while the quality of
the rest of the image is of less importance.
[0009] One method, which can be used, for coding of still images is
the wavelet based S+P transform. The S+P transform is completely
reversible and can be performed directly without memory expansion.
The S+P transform is described in A. Said and W. A. Pearlman,
`Reversible image compression via multiresolution representation
and predictive coding`, in Proc. SPIE Conf. Visual Communications
and Image Processing '93, Cambridge, Mass., Nov. 1993, Proc. SPIE
2094, pp. 664-674, which is incorporated herein by reference.
[0010] It consists of the S transform, see V. K Heer and H-E.
Reinfelder, `A comparison of reversible methods for data
compression`, Proc. SPIE, vol. 1233 Med. Imag. IV, pp 354-365,
1990., which also is incorporated herein by reference and which is
a pyramid sub band decomposition, and of a prediction used to take
out the remaining redundancies from the high frequency sub bands.
The forward transformation is done by applying a subband
decomposition several times. The inverse is found by applying the
corresponding compositions in reverse order.
[0011] In J. Strom, P. C. Cosman, `Medical image compression with
lossless regions of interest`, Signal Processing 59, Nr 2, Jun.
(1997) 155-171 it is described how a lossless region of interest
can be calculated for the S transform.
[0012] However, when trying to apply such a technique to the
wavelet based S+P transform, i.e. lossless transmission of the
region of interest and a lossy transmission of the rest of the
image, no straightforward technique can be used.
[0013] Thus, today there exist no way for lossless region of
interest coding of an S+P transformed image. This is due to the
fact that it is not easy to select the information in the S+P
transformation coded original image which should be transmitted in
order to obtain a perfect, lossless reconstruction of the region of
interest, without having to transmit the entire image lossless.
SUMMARY
[0014] It is an object of the present invention to solve the
problem of how to select the data in an S+P transformed image in
order to achieve a lossless region of interest in a receiver.
[0015] This object is obtained by means of calculating a mask for
the region of interest as will be described below.
[0016] Thus, in order to achieve a perfectly reconstructed region
of interest, while maintaining a fair amount or compression, bits
need to be saved by sending less information about the background
or the part of the image which is not interesting, or at least wait
with that information until a later stage in the transmission.
[0017] To do this, a lossless mask is calculated. The mask is a bit
plane indicating which wavelet coefficients have to be exactly
transmitted if the receiver should be able to reconstruct the
desired region perfectly. In the case that an ROI in the image is
chosen to be lossless, the A-predictor used in the S+P transform
referred to above should be used.
[0018] This is because when the A-predictor is used no prediction
of high frequencies is performed with the help of high frequencies.
If this was the case, like in the C-predictor case, see the
reference above, a possible error might propagate all the way to
the edge of the image, and also inside the ROI, making it
unfeasible to provide a lossless ROI.
[0019] The mask is calculated following the same steps as the
forward S+P transform, i.e. tracing the inverse transform
backwards. To start out with, the mask is a binary map of the ROI,
so that it is 1 inside the ROI and 0 outside. In each step it is
then updated line by line and then column by column. In each step
the mask is updated so that it will indicate which coefficients are
needed exactly at this step, for the inverse S+P to reproduce the
coefficients of the previous mask exactly.
[0020] The last step of the inverse S+P is a composition of two sub
bands. To trace this step backwards, the coefficients in the two
sub bands that are needed exactly are found. The second last step
is a composition of four sub bands into two. To trace this step
backwards, the coefficients in the four sub bands that are needed
to give a perfect reconstruction of the coefficients included in
the mask for two sub bands are found.
[0021] All steps are then traced backwards to give a mask that
implicates the following:
[0022] If the coefficients corresponding to the mask are
transmitted and received exactly, and the inverse S+P (with the
A-predictor) calculated on them, the desired ROI will be
reconstructed perfectly.
[0023] To trace a step backwards on a separate line, where
X.sub.m(n) is the mask before the step inversion, L.sub.m(n) and
H.sub.m(n) are the masks for the low and high frequency sub band
afterwards, the following steps are carried out:
[0024] For the S+P with the A predictor: 1 For all n in [ 1 - N 2 ]
do : H m ( n ) = 1 If { X m ( 2 n ) = 1 } OR { X m ( 2 n + 1 ) = 1
} , 0 otherwise L m ( n ) = 1 If { X m ( 2 n - 2 ) = 1 } OR { X m (
2 n - 1 ) = 1 } OR { X m ( 2 n ) = 1 } OR { X m ( 2 n + 1 ) = 1 }
OR { X m ( 2 n + 2 ) = 1 } OR { X m ( 2 n + 3 ) = 1 } , 0
otherwise
[0025] Thus, the binary mask for the low frequency sub band and the
high frequency sub band, respectively is set to a binary one, i.e.
the corresponding coefficient is to be transmitted in order to
obtain a lossless region of interest, if the above conditions are
fulfilled.
[0026] For synchronisation, the same mask is found both in the
encoder and the decoder. After a certain stage, skipping can be
switched on and background list entries detected. These are the
ones corresponding to sets containing no coefficients that are
indicated for exact transmission by the lossless mask.
[0027] The background list entries can then be skipped totally, put
in a wait list for later improvement or given a lower priority in
some kind of interleaving scheme.
[0028] Furthermore, the shape of the ROI does not have to be
defined before the transmission and can therefore be specified
either by the transmitter or the receiver at any stage of the
transmission.
[0029] The ROI can also be formed by two or more parts, which are
not in contact with each other. The technique is then applied in
the same manner.
BRIEF DESCRIPTION OF THE DRAWINGS
[0030] The present invention will now be described in more detail
by way of a non-limiting examples and with reference to the
accompanying drawings, in which:
[0031] FIG. 1 is a general transmission system employing the S+P
transform.
[0032] FIGS. 2a and 2b are flow charts illustrating different steps
when coding the region of interest for an S+P transformed still
image.
[0033] FIGS. 3a -3e are illustrations of the calculation of a
lossless mask for different sub band stages.
DESCRIPTION OF PREFERRED EMBODIMENTS
[0034] In FIG. 1 a general transmission system employing the S+P
transform is shown. The system comprises an S+P coder block 101,
which is connected to an ROI coding block 103. The S+P block 101
encodes an input image according to the S+P transform referred to
above. The coder 101 can receive information on a particular part
of the image, which is interesting, i.e. the region of interest
(ROI) from a receiver or decoder 107 over a channel 105.
[0035] The information is then forwarded to the ROI block 103 which
calculates the coefficients of the S+P transformed image which
should be transmitted in order to provide the decoder 107 with a
lossless region of interest. The decoder 107 is connected to a
block 109 wherein corresponding ROI decoding can be performed.
[0036] In FIGS. 2a and 2b flow charts illustrating the different
steps, which are carried out in the ROI block 103 in FIG. 1 when
calculating the region of interest for an S+P transformed still
image, are shown.
[0037] Thus, in the ROI block 103 in FIG. 1, the following coding
is executed. First the coding process is started in a block 201.
Then, in a block 203 the calculation of an ROI mask is initiated.
Thereupon, in a block 205 the horizontal sub band length is set
equal to the horizontal image size and the vertical sub band length
is set equal to the vertical image size.
[0038] Next, in a block 207 the first sub band level, corresponding
to the first level of the transform, that is the highest frequency
octave of bands, is looked at, and the procedure proceeds to a
block 209 in which the first horizontal line is looked at.
Thereupon, in a block 211 the horizontal line is updated. The
updating procedure is described in more detail below in conjunction
with FIG. 2b.
[0039] Next, in a block 213 the horizontal line number is
incremented by one and then in a block 215 it is checked if the
horizontal line number is smaller than or equal to the vertical sub
band length. If this is the case the process returns to the block
211 and else it proceeds to a block 217.
[0040] In the block 217, the first vertical line number is looked
at. Next in a block 219, the vertical line number is updated
according to the procedure described below in conjunction with FIG.
2b.
[0041] Thereupon, in a block 221 the vertical line number is
incremented by one, and next, in a block 223, it is checked if the
vertical line number is smaller than or equal to the vertical sub
band length. If this is the case the process returns to the block
219 and else it proceeds to a block 225.
[0042] In the block 225 the horizontal sub band length and the
vertical sub band length are both divided by two. Thereupon in a
block 227 it is checked if this was the last level. If this is the
case the process proceeds to a block 229 in which the process stops
and else it returns to the block 209.
[0043] In FIG. 2b the procedure executed in the blocks 211 and 219
in FIG. 2a is described more in detail. Thus, the procedure starts
in a block 251. Then in a block 253 a parameter n corresponding to
the order number in the line to be updated is set to zero. Next in
a block 255 it is evaluated if the coefficient number n in the line
to be updated is required for obtaining a lossless ROI because it
is required for the prediction of the coefficients (2n-2), (2n-1) ,
(2n) , (2n+1) , (2n+2) and (2n+3).
[0044] Thus, if the mask before the step inversion is a binary one
for (2n-2), (2n-1), (2n), (2n+1), (2n+2) or (2n+3), the procedure
proceeds to a block 257 and else it proceeds to a block 259. In the
block 257, the coefficient n in the line which is currently updated
is set to a binary one (ON), i.e. the coefficient is needed for
obtaining a lossless ROI, and in the block 259 the coefficient n in
the line which is currently updated is set to a binary zero (OFF).
Next the procedure proceeds from the blocks 257 and 259,
respectively to a block 261.
[0045] In the block 261 it is checked if the coefficient number
(n+m/2), where m is the length of the line which is currently
updated is needed for obtaining a lossless ROI. If the evaluation
in the block 261 results in a yes the procedure proceeds to a block
263 and else it proceeds to a block 265.
[0046] In the block 263 the coefficient number (n+m/2) in the line
which is currently updated, is set to a binary one (ON) and the
procedure then proceeds to a block 267. In the block 265 the
coefficient number (n+m/2) in the line which is currently updated,
is set to a binary zero (OFF) and the procedure then proceeds to
the block 267.
[0047] In the block 267 n is incremented by one and the procedure
then proceeds to a block 269. In the block 269 it is checked if n
is smaller than the line length divided by 2, i.e. if n<m/2. If
this is the case the procedure returns to the block 255 and else
the procedure proceeds to a block 271 in which the procedure
stops.
[0048] The method of calculating the lossless mask for the region
of interest can also be expressed as pseudo code as is shown
below.
1 update_line(line) { for(n=0;n<line_length/2;n++) { if
argument_line[2n-2] OR argument_line[2n-1] OR argument_line[2n ] OR
argument_line[2n+1] OR argument_line[2n+2] OR argument_line[2n+3] {
/*turn on low*/ return_line[n]=ON; } else return_line[n]=OFF; if
argument_line[2n ] OR argument_line[2n+1] { /*turn on high*/
return_line[n+line_length/2]=ON; } else
return_line[n+line_length/2]=OFF; } } Make_lossless_mask {
Make_ROI_mask( );/*obtain a mask of the ROI in the image plane*/
/*level loop*/ horizontal_subband_length=horizontal- _image_size;
vertical_subband_length=vertical_image_size;
for(all_levels_of_the_transform) { /*horizontal split*/
for(line=0;line<vertical_subband_le- ngth;line++) {
update_horizontal_line(line)- ; } /*vertical split*/
for(line=0;line<horizontal_subband_length;line++) {
update_vertical_line(line); } horizontal_subband_length/=2;
vertical_subband_length/=2; } }
[0049] In FIGS. 3a -3e, the binary bit masks obtained for different
levels or stages are illustrated. Thus in FIG. 3a the mask of the
desired ROI in the image plane is shown, e.g. the region
transmitted from the receiver to the transmitter in the description
above.
[0050] In FIG. 3b the binary mask for the coefficients needed at
the second sub band stage is shown.
[0051] In the FIGS. 3c -3e the corresponding masks for the fourth,
fifth and seventh sub-band stages are shown, respectively.
[0052] In another preferred embodiment the prediction is extended
to using the low frequency coefficients L(n-2), L(n-1), L(n) ,
L(n+1), L(n+2) . The prediction is therefore:
P(n)=a.sub.n-2*L(n-2)+a.sub.n-1* L(n-1)+a.sub.n* L(n)+a.sub.n+1*
L(n+1)+a.sub.n+2* L(n+2)+a.sub.0
[0053] For example if the coefficients are:
a.sub.n-2=-3/64
a.sub.n-1=22/64
a.sub.n=0
a.sub.n+1=-22/64
a.sub.n+2=3/64
a.sub.0=-32/64
[0054] the filter is identical to the Two-Ten transform used in the
CREW as described in RICOH CREW Image Compression Standard Version
0.11 (Draft 11), 24 Oct. 1997, RICOH Silicon Valley, Inc. If the
coefficients an-2 and an+2 are equal to 0 the predictor will be the
A-predictor. Predictors using more coefficients are also
possible.
[0055] The mask that is found by a backward trace is now slightly
extended. To trace a step backwards on a separate line in this
case, where X.sub.m(n) is the mask before the step inversion,
L.sub.m(n) and H.sub.m(n) are the masks for the low and high
frequency sub band afterwards, the following rules are applied:
[0056] For the extended predictor: 2 For all n in [ 1 - N 2 ] do :
H m ( n ) = 1 If { X m ( 2 n ) = 1 } OR { X m ( 2 n + 1 ) = 1 } , 0
otherwise L m ( n ) = 1 If { X m ( 2 n - 4 ) = 1 } OR { X m ( 2 n -
3 ) = 1 } OR { X m ( 2 n - 2 ) = 1 } OR { X m ( 2 n - 1 ) = 1 } OR
{ X m ( 2 n ) = 1 } OR { X m ( 2 n + 1 ) = 1 } OR { X m ( 2 n + 2 )
= 1 } OR { X m ( 2 n + 3 ) = 1 } OR { X m ( 2 n + 4 ) = 1 } OR { X
m ( 2 n + 5 ) = 1 } , 0 otherwise
[0057] Simple pseudo code for calculating the extended mask is
shown below.
2 update_line(line) { for(n=0;n<line_length/2;n++) { if
argument_line[2n-4] OR argument_line[2n-3] OR argument_line[2n-2]
OR argument_line[2n-1] OR argument_line[2n ] OR argument_line[2n+1]
OR argument_line[2n+2] OR argument_line[2n+3] OR
argument_line[2n+4] OR argument_line[2n+5] { /*turn on low*/
return_line[n]=ON; } else return_line[n]=OFF; if argument_line[2n ]
OR argument_line[2n+1] { /*turn on high*/
return_line[n+line_length/2]=ON; } else
return_line[n+line_length/2]=OFF; } } Make_lossless_mask {
Make_ROI_mask( );/*obtain a mask of the ROI in the image plane*/
/*level loop*/ horizontal_subband_length=horizontal- _image_size;
vertical_subband_length=vertical_image_size;
for(all_levels_of_the_transform) { /*horizontal split*/
for(line=0;line<vertical_subband_le- ngth;line++) {
update_horizontal_line(line)- ; } /*vertical split*/
for(line=0;line<horizontal_subband_length;line++) {
update_vertical_line(line); } horizontal_subband_length/=2;
vertical_subband_length/=2; } }
[0058] Also, it is possible to change the form, size and location
of the region of interest during transmission when using the method
and device as described herein. The only steps that need to be
performed is transmission of a request for another region of
interest from the receiver to the transmitter, which then can
calculated a new mask corresponding to the new region of interest
and then transmit the coefficient corresponding to this new mask to
the receiver. The request for another region of interest can also
be generated at another location than in a receiver, for example by
a program in the transmitter.
[0059] Such a function can be very useful in many applications. It
is, for example, not always that the receiver receives the region
of interest that he/she desires. In that case he/she can transmit a
request for a larger region of interest or even a completely
different region of interest.
[0060] Therefore, in a preferred embodiment, the transmitter is
provided with means for receiving a new region of interest from,
for example, a receiver during transmission of an image, and for
calculating a mask corresponding to such a new region of interest.
A new region of interest can then be transmitted from the
transmitter to the receiver.
[0061] Thus, a method and a device for transmission of S+P
transform coded digitized images using a mask by means of which a
region of interest (ROI) can be transmitted lossless without having
to transmit the remaining part of the digitized image has been
described. The use of the mask makes it possible to transmit and
receive the ROI lossless and still maintaining a good compression
ratio for the image as a whole. This is possible since no or very
few bits can be used for the remaining part of the image.
[0062] Furthermore, a mask calculated according to the principles
described herein can be used for transmitting the coefficients
required for obtaining a lossless ROI at any time during the
transmission.
* * * * *