# Patent

## Title
Color image data compression

## Abstract

Color image data is compressed by determining the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; in response to determining that the number of colors is greater than a first predetermined threshold, compress the cell using lossy compression; and in response to determining that the number of colors is less than the first predetermined threshold, reduce the number of colors.

## Background
PRIORITY
This application is a Continuation of commonly assigned and co-pending U.S. patent application Ser. No. 13/556,198, having a filing date of Jul. 24, 2012, and entitled “COLOR IMAGE DATA COMPRESSION,” the disclosure of which is hereby incorporated by reference in its entirety.


BACKGROUND TO THE INVENTION
Color image data compression is widely used in reducing the data for use with color printers. The color image data is compressed to minimise the data transfer requirements for the printer whilst maintaining image quality and avoiding imaging defects. Many techniques have been developed to compress RGB, most are tuned for images, which preserve too many details that cannot be reproduced by a printing device, and in addition require relatively extensive computation resources. These techniques tend to achieve poor results in compression of high definition graphics. A general purpose compression technique targeted for printing devices should preserve both graphics and images in good quality.



BRIEF DESCRIPTION OF DRAWINGS
For a more complete understanding, reference is now made to the following description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flowchart of an example of a method of compressing color image data
FIG. 2a is a flowchart of an example of reducing the number of colors of the method illustrated in FIG. 1;
FIG. 2b is a flowchart of an alternative example of reducing the number of colors of the method illustrated in FIG. 1;
FIG. 3 is a flowchart of an example of the block of compressing the cell of the method of FIG. 1;
FIG. 4 is a simplified schematic of an example of apparatus for compressing color image data;
FIG. 5 is a graphical representation of the range of compression ratios achieved by the method illustrated in FIG. 1 with 4 colors allowed; and
FIG. 6 is a graphical representation of the range of compression ratios achieved by the method illustrated in FIG. 1 with 2 colors allowed.



DETAILED DESCRIPTION
With reference to FIG. 1, the method 100 of compressing color image data comprises determining the number of colors within a cell of an input image, block 101. Each cell comprises an N×M array of pixels. A pixel is an image element. In the specific example of an RGB image, each pixel is coded using a 24 bit format representing (R, G, B) values. In the specific example, N=M=4. Of course any suitable size cell may be utilised.
Next the determined number of colors is compared with a first predetermined threshold value th1, block 103. If the number of colors is greater than the first predetermined threshold th1, then the cell is compressed using a lossy compression algorithm, like for example, color cell compression, block 105. The first predetermined threshold th1 may be less than or equal to the number of pixels (N*M) in a cell, for example, N=M=th1=4. Once the cell is compressed, block 105 is completed, the compression process ends, step 111. The compressed color image is output and forms the basis for encoding the image for storage and/or printing.
If the number of colors is less than or equal to the first predetermined threshold th1, the number of colors is reduced, block 109, or alternatively, the cell is compressed losslessly. One example of reducing the number of colors is illustrated in FIG. 2a. If the number of colors is less than or equal to the first predetermined threshold th1, the difference (distance) between the colors is determined and if the difference (distance) is less than or equal to a second predetermined threshold th2, block 202, the number of colors is reduced, block 204. The distance between the colors may be any distance function (metric) between two pixels. Any metric may be utilised, but in the specific example the Manhattan distance (block distance) metric is used:

distance(a,b)=|Ra−Rb|+|Ga−Gb|+|Ba−Bb|

The number colors may be reduced, block 204, by averaging the colors of the pixels that have a distance less than or equal to the second predetermined threshold th2 to combine them into a single color. This may be achieved by clustering the colors of the cell and determining the cluster centre of mass and determining the respective distances of the colors of each color with respect to the determined cluster centre of mass. Once the colors have been reduced, the compression process ends, block 111. The reduced color image is output and forms the basis for encoding the image for storage and/or printing.

If the distance between the colors of the cell is greater than the second predetermined threshold th2, block 107, the compression process ends, block 111. The current colors of the cell are output and form the basis for encoding the image for storage and/or printing.
If, in a specific example, the basic cell is 4×4 pixels; each pixel is an RGB color. It is considered that graphic features of an image within such a cell are unlikely to have more than 4 colors, and even if more than 4 colors do exist, they would be impossible to reproduce by known printing techniques. Therefore, any 4×4 cell which contains more than 4 RGB colors, i.e. the number of colors exceed the first predetermined threshold th1 is regarded as an image, and is thus lossy compressed, block 105, and as illustrated in FIG. 3. The lossy compression compresses the colors of the 4×4 cell into either 1 or 2 RGB colors.
Alternatively, as shown in FIG. 2b, if in block 103 of FIG. 1, if the number of colors is determined to be less than or equal to the first predetermined threshold th1, and the number of colors C is 1, block 201, the compression process ends and the one color is encoded, block 203.
If the number of colors, C is determined to be 2, and if either color is black, white or transparent, block 206, then the compression process ends and the two colors are encoded, block 209. If either color is not black, white or transparent, block 206, the distance between the colors is determined, block 207, and if the distance is less or equal to than a third predetermined threshold th3, the 2 colors are combined into a single color by averaging the colors, block 211. The single combined color is then output and the compression process ends and the one color is encoded, block 213. If the distance is greater than the third predetermined threshold th3 then the compression process ends and the two colors are encoded, block 209.
If the number of colors C is greater than 2 but less than or equal to the first predetermined threshold th1, and if the colors are black, white and transparent, then the compression process ends and the original number of colors are encoded, block 220. If at least one of the color is not black, white or transparent, a color cell compression (CCC) cell is created, block 215, by applying the color cell compression algorithm to the cell as described below with reference to FIG. 3.
If all distances between the original cell and the CCC cell are less than or equal to a fourth threshold th4, block 217, then the compression process ends and the cell is encoded as the CCC cell, block 219. Otherwise, it is encoded as the original cell, block 221.
As illustrated in FIG. 3, the lossy compression comprises calculating the luminance of each pixel of the cell, block 301. The cell is then block truncated into 2 colors according to the calculated luminance channel and its truncation into 2 gray levels, block 303. New RGB values for the 2 colors are calculated by averaging, block 305. Up to this point it is the original color cell compression. Next another quantization process is applied to further reduce data. This is achieved by comparing the distance between the 2 colors, block 307. If the distance between the 2 colors is less than or equal to the fifth predetermined threshold th5, the 2 colors are reduced to a single color by averaging, block 309. Otherwise, the cell is preserved with 2 colors.
Further, each pixel of each cell may be classified as transparent, white, black, gray or color. Transparent, white, black and gray pixels are coded using pre-existing codes. Transparent, white and black requires a single code with no additional data, gray requires an additional byte. Color requires additional 3 bytes.
The cell may be further compressed by giving shorter codes to the common black, white, transparent and gray pixels.
RGB data streams may be yet further compressed by using run-length encoding over sequences of identical cells.
The Lossy-ness can be further controlled by changing the value of the second, third, fourth and fifth predetermined thresholds, for example, increasing the second, third, fourth and fifth predetermined threshold levels results in more RGB colors being merged into fewer colors (more lossy-ness). Controlling lossy-ness may be important where size and bandwidth are critical or the application allows more lossy-ness. As an example: compression of images can be safely done with limitation to produce up to 2 RGB colors per cell.
For encoding the pixels of an image, an RGB color may be one of the following kinds:

    
    
        0. Transparent
        1. White-(r,g,b)=(1,1,1)
        2. Black-(r,g,b)=(0,0,0)
        3. Gray-r=g=b
        4. RGB
    
    


An RGB cell may contain up to 4 colors:
Up to one color of Transparent, White and Black
Up to four colors of Gray and RGB.
RGB cell is encoded using the following fields:

    
    
        1. Number of colors
        2. Colors combination code
        3. Vector
    
    


Number of colors per cell can be 1-4, 2 bits are used to encode the number of participating colors as 4-number of colors.
There are 28 possible color combinations stored using 5 bits. The following tables describe possible cell codes:







TABLE 1







Color Codes








Color Code
Color





0
Transparent


1
White


2
Black


3
Gray


4
RGB
















TABLE 2







RGB Cell Codes










Code
Colors







0x00
0123



0x01
0124



0x02
0133



0x03
0134



0x04
0144



0x05
0233



0x06
0234



0x07
0244



0x08
0333



0x09
0334



0x0a
0344



0x0b
0444



0x0c
1233



0x0d
1234



0x0e
1244



0x0f
1333



0x10
1334



0x11
1344



0x12
1444



0x13
2333



0x14
2334



0x15
2344



0x16
2444



0x17
3333



0x18
3334



0x19
3344



0x1a
3444



0x1b
4444










    
    
        C7-0
        
            C6..C5 holds the number of colors n=4−C(6..5)
            C4..C0 holds the color combination in the following way:
        
        
        0—A transparent pixel—up to 1 in a cell, no need for a value
        1—A White pixel—up to 1 in a cell, no need for a value
        2—A Black pixel—up to 1 in a cell, no need for a value
        3—A Gray pixel—up to 4 in a cell, 1 byte is needed to store value
        4—An RGB pixel—up to 4 in a cell, 3 bytes are needed to store value
        Code 0=0x00=0123
        Code 1=0x01=0124
        Code 2=0x02=0133
        Code 3=0x03=0134
        Code 4=0x04=0144
        Code 5=0x05=0233
        Code 6=0x06=0234
        Code 7=0x07=0244
        Code 8=0x08=0333
        Code 9=0x09=0334
        Code 10=0x0a=0344
        Code 11=0x0b=0444
        Code 12=0x0c=1233
        Code 13=0x0d=1234
        Code 14=0x0e=1244
        Code 15=0x0f=1333
        Code 16=0x10=1334
        Code 17=0x11=1344
        Code 18=0x12=1444
        Code 19=0x13=2333
        Code 20=0x14=2334
        Code 21=0x15=2344
        Code 22=0x16=2444
        Code 23=0x17=3333
        Code 24=0x18=3334
        Code 25=0x19=3344
        Code 26=0x1a=3444
        Code 27=0x1b=4444
    
    


eg. 01110000=>4−3=1 colors+16=>WHITE
eg. 01010001=>4−2=2 colors+17=>WHITE+GRAY. The Gray value should follow.
eg. 00001101=>4−0=4 colors+13=>WHITE+BLACK+GRAY+RGB. The Gray and RGB values should occupy the next 4 bytes.
An example of apparatus for compressing color image data is illustrated in FIG. 4. The apparatus 400 comprises an input terminal 401 for receiving a RGB image data stream. The input terminal 401 is connected to a divider 403 for dividing the array of pixels of the image into a plurality (n) of N×M array of pixels or cells. The output of the divider 403 is connected to the input of a classifier 405 for classifying each pixel of the image as transparent, white, black, gray or color. The output of the classifier is connected to the input of a processor 407. The processor may be connected to a storage device 409. The processor 407 is configured to determine the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; in response to determining that the number of colors is greater than a first predetermined threshold, compress the cell using lossy compression; in response to determining that the number of colors is less than the first predetermined threshold, reduce the number of colors. The output of the processor 407 is connected to an output terminal 408. The output terminal 408 provides the output of the compression process which may be provided to an encoder 411 which may be in communication with the storage device 409. The encoder encodes the pixels according to the compression of the colors using codes stored in the storage device 409. The storage device 409 may be utilised to store the final encoded, compressed data or the encoded data may be utilised by a printer to print the compressed image.
As illustrated in table 3 below, the method of the examples of FIGS. 1 to 3 was tested on a set of 21 images, 0.tif, 1.tif, 2.tif . . . 20.tif containing a wide variety of graphics, natural images and test features. The images were sent to a CMYK-based printer, and the raster output in CMYK of the printer was captured at machine resolution of 32 dpmm. It was then converted to RGB and processed using a matrix of distance values for th2, th3, th4 and th5 of 0, 10, 20, 50, 100 and of permitted colors of 2 or 4 (i.e. th1). The images were printed on a CMYK-based printer by converting them to CMYK and compressing the cells as described above. After that, they were inspected for artifacts and their compression ratio was captured.
The best, worst and average values of table 3 below are illustrated graphically for 4 permitted colors in FIG. 5 and for 2 permitted colors in FIG. 6.







TABLE 3







Compression ratio results table










Max 4 colors
Max 2 colors

















Image
0
10
20
50
100
0
10
20
50
100




















10.tif
28.42%
19.49%
15.81%
11.41%
9.31%
16.67%
14.40%
12.91%
10.66%
9.38%


 6.tif
27.88%
21.79%
16.47%
10.96%
8.89%
16.37%
14.69%
12.33%
9.65%
8.26%


17.tif
20.13%
8.53%
7.11%
6.61%
6.47%
13.05%
10.36%
9.56%
9.24%
9.14%


 4.tif
16.36%
6.88%
5.86%
5.41%
5.27%
12.61%
10.86%
10.26%
9.96%
9.86%


 0.tif
16.01%
13.44%
11.25%
8.39%
6.57%
9.15%
8.74%
7.91%
6.63%
5.70%


12.tif
14.81%
10.49%
8.23%
6.10%
5.30%
9.56%
8.44%
7.34%
6.09%
5.58%


20.tif
14.67%
10.28%
9.08%
8.32%
8.05%
12.15%
11.48%
11.05%
10.77%
10.65%


16.tif
13.68%
10.90%
8.48%
6.33%
5.44%
9.55%
8.89%
7.39%
5.94%
5.31%


 8.tif
13.65%
9.49%
7.76%
6.13%
5.41%
8.84%
7.97%
7.26%
6.49%
6.10%


11.tif
13.23%
8.82%
6.74%
4.95%
4.26%
7.83%
6.74%
5.80%
4.79%
4.34%


 3.tif
12.96%
8.98%
7.44%
5.82%
4.98%
7.93%
7.14%
6.61%
5.95%
5.53%


19.tif
12.85%
9.08%
6.95%
5.07%
4.34%
7.85%
6.85%
5.86%
4.81%
4.33%


 5.tif
9.72%
6.51%
6.07%
5.89%
5.74%
7.99%
7.55%
7.41%
7.37%
7.32%


18.tif
9.22%
5.30%
5.30%
5.30%
5.30%
8.29%
7.95%
7.95%
7.95%
7.95%


13.tif
8.32%
4.84%
4.73%
4.67%
4.66%
6.86%
6.48%
6.44%
6.41%
6.40%


 7.tif
7.24%
5.63%
4.42%
3.61%
3.56%
4.79%
4.12%
3.53%
3.13%
3.09%


 1.tif
7.21%
4.78%
4.71%
4.65%
4.61%
5.99%
5.63%
5.60%
5.58%
5.57%


 2.tif
6.34%
5.28%
4.46%
3.73%
3.23%
4.11%
3.90%
3.62%
3.39%
3.20%


 9.tif
4.38%
3.50%
2.62%
1.87%
1.73%
3.19%
2.97%
2.41%
1.85%
1.73%


15.tif
2.58%
2.58%
2.58%
2.58%
2.58%
2.58%
2.58%
2.58%
2.58%
2.58%


14.tif
1.34%
1.26%
1.25%
1.24%
1.23%
1.28%
1.27%
1.26%
1.26%
1.25%


Best
1.34%
1.26%
1.25%
1.24%
1.23%
1.28%
1.27%
1.26%
1.26%
1.25%


Average
12.43%
8.47%
7.01%
5.67%
5.09%
8.41%
7.57%
6.91%
6.21%
5.87%


Worst
28.42%
21.79%
16.47%
11.41%
9.31%
16.67%
14.69%
12.91%
10.77%
10.65%









As illustrated above in table 3 and FIGS. 5 and 6, the compression ratio for 2 permitted colors is much better than 4 permitted colors for small threshold values, but the difference becomes negligible at higher threshold values such as above 20.
No artifacts were noticeable in the images compressed using threshold values under 50. At this distance level (50) compression ratios seems to be below 12%. Therefore, it is shown that the method of the examples above is a very good compression method targeted for printing devices which store or transfer their data in RGB.
As a result, the method of the examples above reliably preserves graphics features and maintaining their color accuracy. The method above is relatively simple from computational point of view, and can easily be parallelized. It provides direct scan access and may be used by page composition systems or for texture compression, allowing for fast compression and decompression, random access into image data and asymmetrical processing effort between encoding and decoding. Therefore, it preserves both natural images and synthetic graphics at the desired quality.
It performs well on all RGB based images, as well as Luminance and Chrominance (YUV, YCbCr, Lab, etc) and Hue and Saturation (HSV, HSL) models.
In addition, it can be easily adapted with only minor changes required to be used for RGBA (alpha channel) compression or for compressing other multi-channel color systems such as YUV and Lab. In RGB, Luminance is calculated by Luminance(R,G,B)=0.229R+0.587G+0.114B. In Lab and Yuv, Luminance is given by the L and Y channels. In RGB, gray is defined as R=G=B. In Lab and Yuv, Gray is defined as a=b=0 and u=v=0. The method described above is then applied using these values.
All “Luminance plus Chrominance” color spaces (Lab, Yuv, YIQ, YDbDr, YCbCr YPbPr, where Luminance it the first channel and Gray is defined as the chrominance channels equal zero may be captured. The same also applies for “Hue and Saturation” spaces (HSV HSL) where V/L is luminance and gray is defined as HS equal zero.
Although various examples have been illustrated in the accompanying drawings and described in the foregoing detailed description, it will be understood that the invention is not limited to the examples disclosed, but is capable of numerous modifications without departing from the scope of the invention as set out in the following claims.

## Claims

1. A method comprising;
determining, by a processor, the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; and
in response to determining that the number of colors is greater than a first predetermined threshold, compressing, by the processor, the cell using, loss compression;
in response to determining that the number of colors is less than or equal to the first predetermined threshold, reducing, by the processor, the number of colors by:
determining whether the number of colors is 2;
in response to determining that the number of colors is 2, determining the distance between the two colors;
determining whether the distance between the two colors is less than or equal to a predetermined threshold distance; and
in response to determining that the distance between the two colors is less than or equal to the predetermined threshold distance, averaging the two colors to reduce the number of colors to 1.

2. The method according to claim 1, further comprising:
in response to determining that the number of colors of the cell is greater than 2 but less than or equal to the first predetermined threshold, compressing the cell to create a color cell compression (CCC) cell;
determining all of the distances between the CCC cell and the original cell;
in response to all of the distances being less than or equal to a second predetermined threshold, using the CCC cell; and
in response to at least one of the all of the distances being greater than the second predetermined threshold, using the original cell.

3. The method according to claim 1, wherein compressing the cell using lossy compression comprises compressing the cell using color cell compression.

4. The method according to claim 3, wherein compressing the cell using color cell compression comprises:
block truncating to two colors of each cell having a number of colors greater than a first predetermined threshold according to a luminance level of each pixel of each cell having a number of colors greater than a first predetermined threshold; and
calculating new color values for the two colors by averaging the two colors.

5. The method according to claim 4, wherein compressing the cell further comprises:
in response to determining that the distance between the luminance of the pixels of two colors is less than or equal to a second predetermined threshold, averaging the luminance of the two colors to a single color; and
in response to determining that the distance between the luminances of the pixels of two colors is greater than the second predetermined threshold and in response to determining that the two colors are not to be preserved, reducing the two colors to a single color.

6. The method according to claim 1, further comprising:
one of encoding the pixels of the compressed cell and encoding the pixels having the reduced number of colors.

7. The method according claim 1, wherein each pixel of each cell is classified as transparent, white, black gray or color and the method further comprising:
coding the pixels classified as transparent, white, black or gray using pre-existing codes.

8. An apparatus comprising:
a processor;
a memory on which stored machine readable instructions to cause the processor to:
determine the number of colors within a cell of an input image, each cell comprising an N×M array of pixels;
in response to a determination that the number of colors is greater than a first predetermined threshold, compress the cell using lossy compression;
in response to a determination that the number of colors is less than or equal to the first predetermined threshold, reduce the number of colors, wherein to reduce the number of colors, the machine readable instructions are further to cause the processor to:
determine whether the number of colors is 2;
in response to a determination that the number of colors is 2, determine the distance between the two colors;
determine whether the distance between the two colors is less than or equal to a predetermined threshold distance; and
in response to determining that the distance between the two colors is less than or equal to the predetermined threshold distance, average the two colors to reduce the number of colors to 1.

9. The apparatus according to claim 8, wherein the machine readable instructions are further to cause the processor to:
in response to a determination that the number of colors of the cell is greater than 2 but less than or equal to the first predetermined threshold, compress the cell to create a color cell compression (CCC) cell;
determine all of the distances between the CCC cell and the original cell;
in response to all of the distances being less than or equal to a second predetermined threshold, use the CCC cell; and
in response to at least one of the all of the distances being greater than the second predetermined threshold, use the original cell.

10. The apparatus according to claim 8, wherein the input image comprises an N×M array of pixels, n being a positive integer, and the machine readable instructions are further to cause the processor to divide an image, into n cells of N×M array of pixels.

11. The apparatus according to claim 8, wherein the machine readable instructions are further to cause the processor to classify each pixel of the input image as transparent, white, black, gray or color.

12. The apparatus according to claim 8, wherein the machine readable instructions are further to cause the processor to one of encode the pixels of the compressed cell encode the pixels having the reduced number of colors.

13. A non-transitory computer-readable medium comprising machine readable instnictions that when executed by a processor cause the processor to:
determine the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; and
compress the cell, using lossy compression in response to a determination that the number of colors is greater than a first predetermined threshold; and
reduce the number of colors in response to a determination that the number of colors is less than or equal to the first predetermined threshold, where to reduce the number of colors, the machine readable instructions are further to cause the processor to:
determine whether the number of colors is 2;
in response to a determination that the number of colors is 2, determine the distance between the two colors;
determine whether the distance between the two colors is less than or equal to a predetermined threshold distance; and
in response to determining that the distance between the two colors is less than or equal to the predetermined threshold distance, average the two colors to reduce the number of colors to 1.

14. The non-transitory computer-readable medium according to claim 13, wherein the machine readable instructions are farther to cause the processor to:
one of encode the pixels of the compressed cell in response to determining that the number of colors is greater than a first predetermined threshold and encode the pixels having the reduced number of colors in response to a determination that the number of colors is less than the first predetermined, threshold.