Title of Invention

COLOR IMAGE PROCESSING APPARATUS

Abstract The present invention provides a color image processing method and apparatus for preprocessing of color images required for retrieving a color feature descriptor used in indexing and searching a color image. Using the apparatus of the present invention filtering or noise removal can be performed without edge blurring of the color image and noise in the color image can be eliminated. The color image processing apparatus includes a sorting means for setting a window of a predetermined size within an input color image and sorting image pixels in the window of a predetermined size within an input color image and sorting image pixels in the window according to the color distance between the image pixels and a central pixel, grouping means for grouping the sorted pixels into groups in which the difference in the intergroup color distance is minimum and the difference is maximum and filtering means for performing filtering by replacing a central pixel value with a predetermined pixel value determined by pixel values of pixels in groups.
Full Text Technical Field
The present invention relates to an image processing method, and more particularly, to a color image processing method which is a pre-processing method required for retrieving a color feature descriptor used in indexing and searching a color image.
Background Art
In object-based digital image compression standards such as MPEG-7, color feature descriptors for indexing and searching color images are defined. A color feature descriptor is retrieved from an input image.
In the color image processing method, in order to retrieve a color feature descriptor, an input image is segmented into a plurality of regions, quantized color vectors for the segmented regions are obtained, and then the color feature descriptor of a pertinent region is determined using the quantized color vectors. However, noise components may exist in the image. Also, good color quantization is important in accurately representing color information in the image. Thus, pre-processing such as filtering or noise removal is necessarily performed before quantization.
Conventionally, in order to remove noise from an image, filtering methods such as vector median filtering or vector directional filtering have been employed.
However, since filtering method used in conventional color image processing methods are uniformly applied to an image, non-noisy pixels may be modified, which causes edge blurring in the original imase.
Disclosure of the Invention
To solve the above problem, it is an objective of the present invention to irovide a color image processing method and apparatus, by which filtering can be XTformed without cdje blurring of the color image and noise in the color image can x1 eliminated, the method beinu a pre-processing method required for retrieving a
color feature descriptor for indexing and searching the color image.
It is another object of the present invention to provide a computer readable medium having a program executable by a computer to perform the color image processing method.
A feature of the present invention is embodied by a color image processing method includes the steps of (a) sorting image pixels according to the color distance between the image pixels and a central pixel. Xb) grouping the sorted pixels into groups in which the difference in the intragroup color distance is minimum and the difference in the intergroup color difference is maximum, and (c) performing filtering by replacing a central pixel value with a predetermined pixel value determined by pixel values of pixels in the groups.
The color image processing method may further include the step of defining a window having a predetermined size within an input color image, wherein the image pixels are pixels within the window.
Before the step (b), the method preferably further includes the step of removing pixels having a difference in color distance I'rom the central pixel greater than or equal to a predetermined threshold, with respect to a predetermined number of pixels at the beginning and latter pans among the sorted pixels.
The predetermined number is preferably less than or equal to L/2. in which L is a predetermined positive number indicating the size of an LXL window.
Before the step (b). the method preferably further includes the step of removing pixels having a difference in color distance from the central pixel greater than or equal to a predetermined threshold, with respect to a predetermined number of pixels at the beginning and latter parts among the sorted pixels.
Also, the step (b) may include grouping the sorted pixels using a function :>ased on a Fisher's discriminant estimation method.
The step (b) may include the sub-steps of (b-I) setting a first group consisting jf Oth through (i-J)(\\ pixels, and a second group consisting of nh through A'th jixels. wherein / is an integer from 0 through A' and A'=L:- 1. (b-2) obtaining the espective averages of the color distance differences Cor pixels of the first and second :roups by the following Expressions:
(Equation Removed)
. (b-3) obtaining the
respective variances of the color distance differences for pixels of the first and second groups are obtained by the following Expressions:
(Equation Removed)
calculating a value 7(7; by the following Expression, using the obtained average and variance:
(Equation Removed)
. and (b-5) obtaining the value of/ which makes
J(l) maximum hy [he following Expression: (Equation Removed)
. and selecting pixels ranging from a pixel having a
small color distance to a pixel having the obtained value of / to determine the same as a peer group P(n).
Also, after the step (b-5). the method may further include the steps of selecting /pixels ranging from the pixel having the minimum color distance among the pixels soned according to the color distance from the central pixel and setting the largest value of the color distances of the selected pixels as the maximum color distance within the pec'" group, and performing color quantization by weighting the color vectors of the respective pixels by exp(-T(n)), wherein T(n) is the maximum color distance within the peer group.
Alternatively, afier the step (b-5). the method may further include the steps of selecting / pixels ranging from the pixel having the minimum color distance among the pixels sorted according to the color distance from the central pixel and setting the luryesi value ol the color distances of the selected pixels as the maximum color distance within the peer group, and obtaining the average ol'T(n) values ol the
whole image and performing color quantization using a value obtained by multiplying the average with a predetermined constant as the number of clusters, wherein T(n) is the maximum color distance within the peer group.
Also, after the step (b-5). the method may further include the steps of selecting pixels whose number corresponds to the size of the peer group, ranging from the pixel having the minimum color distance among the pixels sorted according to the color distance from the central pixel and setting the largest value of the color distances of the selected pixels as the maximum color distance within the peer group, and weighting the color vectors of the respective pixels by exp(-T(n)). wherein T(n) is the maximum color distance within the peer group, and performing color quantization using a value obtained by multiplying the average of the T(n) values of the whole image with a predetermined constant as the number of clusters.
The step (c) preferably includes replacing the central pixel X0(n) with a new pixel X',,(n) by the following Expression:
(Equation Removed)
where p,(n) are the pixels constituting the peer group and Vy are predetermined weights corresponding top,(n).
Also, the step (c) preferably includes replacing the color vector of the central pixel with an average weighted by a predetermined weight that is larger for a pixel closer to the central pixel and is smaller for a pixel distant from the central pixel.
The predetermined weight is preferably. a value determined by a standard
Gaussian function.
The color image processing method may further include the step of performing color quantization by weighting the color vectors of the respective pixels by e.\p(-T(n)). wherein T(n) is the maximum color distance within one group
According lo another aspect of the present invention, there is provided a color
image processing method including the steps of (a) receiving a color image frame and segmenting the same into a plurality of color images by a predetermined segmentation method, (b) sorting image pixels according to the color distance between the image pixels and a central pixel, with respect to an image selected among the segmented color images, (c) grouping the sorted pixels into groups in which the difference in the intragroup color distance is minimum and the difference in the intergroup color difference is maximum, and (d) performing filtering by replacing a central pixel value with a predetermined pixel value determined by pixel values of pixels in the groups.
According to still another aspect of the present invention, there is provided a color image processing method including the steps of (a) defining a window having a predetermined size within an input color image, (b) selecting pixels having a color vector similar to thai of the central pixel within the window and defining the selected pixels as a group, and (c) performing filtering of blurring using only the pixels within the defined group.
The present invention is also embodied by a computer readable medium having program codes executable by a computer to perform a color image processing method, the method including the steps of (a) defining a window having a predetermined size within an input color image, (b) sorting image pixels according to the color distance between the image pixels and a central pixel, (c) grouping the sorted pixels into groups in which the difference in the intragroup color distance is minimum and the difference in the intergroup color difference is maximum, and (d) performing filtering by replacing a central pixel value with a predetermined pixel value determined by pixel values of pixels in the groups.
Alternatively, the present invention provides a color linage processing apparatus including sorting means tor setting a windrow of a predetermined size within an input color image and son ing image pixels in the window according to the color distance between the image pixels and a central pixel, grouping means for grouping the sorted pixels into groups in which the difference in the intragroup color distance is minimum and die difference in the intergroup color difference is maximum, and filtering means tor performing tillering by replacing a central pixel
value with a predetermined pixel value determined by pixel values of pixels in the groups.
Statement of Invention
Accordingly the present invention relates *o a oolor imago proooooing method comprioing
(a) sorting image pixels according to a color distance between image
pixels and a central pixel,
(b) grouping the sorted pixels into groups in which distance in intragroup
color distance is minimum and a difference irr intergroup color
distance is maximmn and determining at least one peer group among
the groups according to a color distance between the central pixel and
the groups, and
(c) performing filtering by replacing a central pixel value with a pixel
value jrfetermined by using pixel vajoes of pixels in the at least one
pee/group.
a color image processing apparatus comprising:
a sorting unit (202) for setting a window of a predetermined size within an input color image and sorting image pixels in the window according to a color distance between the image pixels and a central pixel,
a grouping unit (206) for grouping the sorted pixels into groups in which a difference in an intragroup color distance is minimum and distance in an intergroup color distance is maximum and determining at least one peer group among the groups according to a color distance between the central pixel and the groups, and
a filtering unit (208) for performing filtering by replacing a central pixel value with a pixel value determined by using pixel values of pixels in the at least one peer group.
a predetermined pixel vaj>rc determinedly pixeLtfalues of^lxels urtfie
Brief Description of the Drawings
The above objects and advantages of the present invention will become more apparent by describing in detail preferred embodiments thereof with reference to the attached drawings in which:
FIGS. 1A and IB are flow diagrams showing a color image processing method according to the present invention: and
FIG. 2 is a block diagram of a color image processing apparatus according to the present invention.
Rest mode for carrying out the Invention
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Referring to FIG. 1A illustrating a color image processing method according to the present invention, a color image is input (step 100). The color image may be in one region selected among image regions segmented by an appropriate segmentation method.
Next, with respect to color vectors of all pixels in a LXL window in an input color image, the color distance djn) from the color vector X(l(n) of a pixel positioned at a position n at the center of the LXL window is represented by Expression (1) (step 102):
(Equation Removed)
A'herein L is an arbitrary positive integer, and assuming that A'=L:- I. / is an integer
rom 0 through K. Also, for convenience' sake of explanation. X,,(n). which
represents the color vector of L'L window in an mpui color image. m;iy he used 10 represent the corresponding
pixel positioned ;u ihe center, dial is ,i central pixel
Next, the corresponding color vectors of all pixels in the window are sorted in an ascending order according to the magnitude of the color distance dt(n) (step 104). Hereinbelow. the color vectors sorted in ascending order will be represented byX,(n).
Now, with respect to the color vectors sorted in ascending order, color distance difference is calculated by Expression (2) (step 106):
and then color vectors in which f,(n) is greater than a predetermined threshold Q are removed (step 108). That is. the color vectors in which f,(n) is greater than a predetermined threshold Q are considered impulse noise to then he removed. According to experimental confirmation, it is more preferably to perform the step 108 with respect to the beginning L/2 pixels and the latter L/2 pixels in ascending
order, than to perform it with respect to all the (L:- 1) pixels in the L---L window.
except of the central pixel X,,(n).
Also, according to the present invention, in order to prevent edge blurring of
an image, filtering is performed on pixels in a peer group to be described later.
rather than on all the pixels in the LXL window. The peer groups are obtained as
follows.
First, the pixels sorted in ascending order according to their color distance
from the color vector of the central pixel are divided into two groups. The first
group consists of Oth through (i-l)ih pixels, and the second group consists of /th
through ATth pixels.
Next, the average of the color distance differences for pixels of the first
group and the average of the color distance differences for pixels of the second group
are obtained as represented by Expressions (3a) and (?h). respectively:
(Equation Removed)
and the variance of the color distance differences for pixels of the first croup and the variance of the color distance difference for pixels of the second group are obtained as represented by Expressions (3c) and (3d), respectively:
(Equation Removed)
wherein / is a newly defined integer ranging from 0 through K.
Then, using the obtained average and variance, a value J(i) represented by Expression (4) is calculated (step 110):
wherein / is an integer ranging from 1 through K. The Expression (4) is based on Fisher's discriminant estimation method.
Here, the actual range of / is from 1 through the numbers obtained by
subtracting the number corresponding to color vectors of the pixels considered as
impulse noise for removal from K. However, since the number corresponding to
' color vectors of the pixels considered as impulse noise and removed is not so large.
it is assumed that the range of/ is from 1 through K.
Next, the value of / which makes J(i) maximum is obtained by Expression (5):
(Equation Removed)
10 then determine the obtained value of/ as the magnitude of a peer group P(n) (step 112). In other words, when / is reset to variables ranging from 0 through the value obtained in (he step 112. the peer group P(n) consists of pixels p,(n)
Referring (o RG. ID. ihc central pixel X,,(n) is replaced with a new pixel

X'0(n) by Expression (6):
(Equation Removed)
where W, are the standard Gaussian weights corresponding to p,(n) (step 114). Here, the standard Gaussian weights Wt are determined by a standard Gaussian function. A pixel closer to the center of an image has a larger standard Gaussian weight and a pixel distant from the center has a smaller standard Gaussian weight. The procedure of replacing pixels in such a manner is smoothing or filtering.
Supposing the maximum color distance in each peer group d..,,,,, ,(n) is T(n). exp(-T(n)) is applied to the color vectors of the respective pixels during color quantization (step 116). The maximum color distance dmim ,(n) in each peer group indicates the largest value of the color distances of pixels whose number correspond to the size of the peer group ranging from the pixel having the minimum color distance, among the pixels soned in ascending order according to their color distance from the central pixel. Thus, the smaller the maximum color distance dm(n) ,(n) in each peer group, the shorter the color distance from the central pixel, so that dniased on the analysis result of eye-perception, that is. the eye-perception is more ;ensitive to changes in detailed regions than in smooth regions.!
According to the present invention, during quantizaiion. the value obtained iy multiplying a predetermined constant with the average of T(n) values of all mages is preferably used as the number of clusters. In other words, during uantization. fewer clusters are used in smooth regions where the T(n) value is mall, and more clusters arc used in highly noisy regions where the T(n) value is iree
In the color image processing method according to the present invention, only the pixels having large color distances from the central pixel are removed, and then a peer group having a color vector similar to that of the central pixel is defined to then perform filtering thereon. Thus, edge blurring of an image rarely occurs due to removal and filtering of impulse noise. Also, according to the present invention, the information on the extent of quantization to be performed on an image can be obtained.
The color image processing method is programmable by a computer program. Codes and code segments constituting the computer program can be easily derived by a computer programmer in the an. Also, the program is stored in computer readable media and is readable and executable by the computer, thereby embodying the color image processing method. The media include magnetic recording media, optical recording media, carrier wave media, and the like.
Also, the color image processing method can be implemented on a color image processing apparatus. FIG. 2 is a block diagram of a color image processing apparatus according to the present invention. Referring to FIG. 2. the color image processing apparatus according to the present invention includes a segmenting unit 200. a sorting unit 202. an impulse noise removing unit 204. a grouping unit 206. a filtering unit 208 and a quantizing unit 210.
In the operation of the color image processing apparatus, the segmenting unit 200 receives a color image frame and segments the color image frame into a plurality of color images by a predetermined segmentation method.
The sorting unit 202 sets an L*L window (L is a predetermined positive integer.) within the color images, and sorts the pixels within the window according to the color distance between each pixel and the central pixel. Thus, the sorting umi 202 outputs color vectors of the sorted pixels.
The impulse noise removing unit 204 removes the pixels thai have a difference in color distance from the central pixel greater than a predetermined threshold, with respect to the beginning L/2 pixels and (he latter L/2 pixels among ihe sorted pixels.
The grouping unit 206 receives color vectors ol all (he noise-removed pixeK
in the LXL window and divides the same into two groups in which the difference in the intragroup color distance is minimum and the difference in the intergroup color difference is maximum, by calculating the function represented by the Expression (4) using the variance and average of the color distances between the sorted pixels.
The filtering unit 208 performs filtering by replacing the central pixels with pixels in a group having a small difference from the color vector of the central pixels in the window.
The quantizing unit 210 weights the color vectors of the respective pixels by exp(-T(n)), in which T(n) is the maximum color distance within a group having a small difference in the color vector from the central pixel within the window, and performs quantization using the value obtained by multiplying a predetermined constant with the average of T(n) values of all images as the number of clusters.
In the above-described color image processing apparatus according to the present invention, since the pixels having large color distances from the central pixel are removed, a peer group having a color vector similar to that of the central pixel is defined to then perform filtering thereon. Thus, edge blurring of an image rarely occurs due to removal and filtering of impulse noise. Also, according to the present invention, the information on the number of clusters for quantization to be performed can be obtained based on the smoothness or details of an image to be processed. Thus, quantization is can be effectively performed using the information. As described above, according to the present invention, in removing impulse noise from an image and filtering the same, the generation of edge blurring of the imase can be reduced.
Industrial Applicability
The present invention can be applied to the fields of color image indexing or searching applications.



We claim:
1. A color image processing apparatus comprising:
a sorting unit (202) for setting a window of a predetermined size within an input color image and sorting image pixels in the window according to a color distance between the image pixels and a central pixel,
a grouping unit (206) for grouping the sorted pixels into groups in which a difference in an intragroup color distance is minimum and distance in an intergroup color distance is maximum and determining at least one peer group among the groups according to a color distance between the central pixel and the groups, and
a filtering unit (208) for performing filtering by replacing a central pixel value with a pixel value determined by using pixel values of pixels in the at least one peer group.
2. The color image processing apparatus as claimed in claim 1, comprising
quantizing unit (210) for performing color quantization by weighting the color
vectors of the respective pixels by exp (-T (n)), wherein T (n) is the maximum
color distance within a group having the smallest difference in the color vector
from the central pixel within the window.
3. The color image processing apparatus as claimed in claim 1, comprising
quantizing unit (210) for obtaining the average of T (n) values of the whole image
and performing color quantization using a value obtained by multiplying the
average with a predetermined constant as the number of clusters, wherein T (n) is
the maximum color distance within a group having the smallest difference in the
color vector from the central pixel within the window.
4. The color image processing apparatus as claimed in claim 1, comprising
quantizing unit (210) for weighting the color vectors of the respective pixels by
exp (-T (n)), and performing color quantization using a value obtained by
multiplying the average of T (n) values of the whole image with a predetermined
constant as the number of clusters, wherein T (n) is the maximum color distance
within a group having the smallest difference in the color vector from the central
pixel within the window.
5. The color image processing apparatus as claimed in claim 1, comprising an
impulse noise removing unit (204) for removing pixels having a difference in the
color distance from the central pixel greater than or equal to a predetermined
threshold, with respect to a predetermined number of pixels at the beginning and
latter parts among the sorted pixels.
6. The color image processing apparatus as claimed in claim 1, comprising a
segmenting unit (200) for receiving a color image frame and segmenting the same
into a plurality of color images by a predetermined segmentation method, wherein
the color image is an image selected from the plurality of color images.
7. A color image processing apparatus substantially as herein described with
reference to the accompanying drawings.

Documents:

in-pct-2001-00666-del-abstract.pdf

in-pct-2001-00666-del-claims.pdf

in-pct-2001-00666-del-correspondence-others.pdf

in-pct-2001-00666-del-correspondence-po.pdf

in-pct-2001-00666-del-description (complete).pdf

in-pct-2001-00666-del-drawings.pdf

in-pct-2001-00666-del-form-1.pdf

in-pct-2001-00666-del-form-13.pdf

in-pct-2001-00666-del-form-19.pdf

in-pct-2001-00666-del-form-2.pdf

in-pct-2001-00666-del-form-26.pdf

in-pct-2001-00666-del-form-3.pdf

in-pct-2001-00666-del-form-5.pdf

in-pct-2001-00666-del-pct-101.pdf

in-pct-2001-00666-del-petition-137.pdf

in-pct-2001-00666-del-petition-138.pdf


Patent Number 231778
Indian Patent Application Number IN/PCT/2001/00666/DEL
PG Journal Number 13/2009
Publication Date 27-Mar-2009
Grant Date 09-Mar-2009
Date of Filing 25-Jul-2001
Name of Patentee SAMSUNG ELECTRONICS CO., LTD.
Applicant Address 416, MAETAN-DONG, PALDAL-GU SUWON-CITY, KYUNGKI-DO, 442-373, REPUBLIC OF KOREA.
Inventors:
# Inventor's Name Inventor's Address
1 HYUN-DOO SHIN 510-1302 MUJIGAE MAEUL CHEONGGU APT., 221 KUMI-DONG BUNDANG-GU, SUNGNAM-CITY, KYUNGKI-DO 463-500, REPUBLIC OF KOREA.
2 YANG-LIM CHOI 102-1112 WOOMAN SUNKYUNG APT., 105 WOOMAN-DONG PALDAL-GU, KYUNGKI-DO, 442-190 REPUBLIC OF KOREA.
3 YINING DENG DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING, UNIVERSITY OF CALIFORNIA, SANTA BARBARA, CA 93106-9560, U.S.A.
4 B.S. MANJUNATH DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING, UNIVERSITY OF CALIFORNIA, SANTA BARBARA, CA 93106-9560, U.S.A.
PCT International Classification Number G06T 1/00
PCT International Application Number PCT/KR00/00090
PCT International Filing date 2000-02-03
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 60/118,741 1999-02-05 Republic of Korea