JP2003348359A - Color image compressing apparatus and method therefor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a color image compressing apparatus and a method therefor in which no noise is generated on the block boundary of an expanded image while suppressing transmission costs or medium costs with respect to an image wherein a pattern of a gradation system exists over processing unit blocks. <P>SOLUTION: A color image of the gradation system is divided into respective R, G and B planes, a primary difference with respect to data of elements in the respective planes is calculated and further, a secondary difference with respect to the primary difference is calculated to discriminate the presence/non- presence of regularity in the secondary difference. When there is regularity in the secondary difference, a reversible compression scheme of high compressibility specialized for the gradation system is used but when there is no regularity, an irreversible compression scheme is used. Thus, a color image is compressed while reducing the transmission costs or the medium costs and securing a quality in the case of expansion. <P>COPYRIGHT: (C)2004,JPO

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and method for compressing a color image, and more particularly to an image in which a gradation pattern is present over a processing unit block, while suppressing transmission costs or medium costs. The present invention relates to a color image compression apparatus and method for preventing noise from occurring at block boundaries of an expanded image.

[0002]

2. Description of the Related Art Image data existing on a host device is
When the image data is displayed on another display device via a transmission path or a medium, the image data is compressed on the host side and decompressed on the display device to reduce the transmission cost (transmission time or the like) or the medium cost (memory area or the like). A method of suppressing it is taken.
As a method of compressing an image in such a case, JPE
G (Joint Photographic Experts Group)
An irreversible compression method that cannot complement a predicted point after transmission is used. The JPEG method is one of the well-established compression methods that suppresses discomfort when viewed with human eyes in natural images and the like.

[0003]

However, in the compression method using the JPEG method, which is irreversible compression, although the transmission cost or the medium cost can be suppressed, a gradation (graphic) pattern exists across processing unit blocks. In such an image, there is a problem that noise occurs at the block boundary of the developed image.

The present invention has been made in view of the above circumstances, and is an image in which a gradation type pattern is present over a processing unit block. It is an object of the present invention to provide a color image compression apparatus and a method thereof in which noise does not occur at a boundary.

[0005]

According to a first aspect of the present invention, there is provided an image processing apparatus comprising: a display device for displaying image data existing on a host device on another display device via a transmission path or a medium; Compressing the image data on the host device side,
An RGB plane dividing means (21) for dividing the image data into R, G, and B planes in the color image compression apparatus developed on the display device;
Primary difference calculating means (22) for calculating a primary difference of adjacent data in each plane divided by the B plane dividing means (22)
A secondary difference calculation unit (23) for calculating a secondary difference between adjacent data of the primary difference calculated by the primary difference calculation unit;
Regularity detecting means (24) for detecting whether there is regularity between adjacent data calculated by said secondary difference calculating means (24)
When the data detected by the regularity detecting means has regularity, the image data is compressed by a reversible compression method, and when the detected data has no regularity, the image data is irreversible. And a compression method selection means (25) for selecting compression by a compression method.

In the above construction, the secondary difference calculating means (2
When 3) calculates the adjacent data of the primary difference, as shown in FIG. 1, the first, second, and third patterns have regularity, but the fourth pattern has no regularity. The regularity detecting means (24) detects the regularity. The compression method selection means (25) selects a reversible compression method when there is regularity, and selects an irreversible compression method when there is no regularity.

In this way, when there is regularity, a lossless compression method for gradation system (for example, a "color image compression method" having a high compression rate described later) is adopted, so that image quality is not degraded. In addition, transmission costs or medium costs can be reduced. Conversely, when there is no regularity, an irreversible compression method with a high compression ratio (for example, JPEG method) is employed, so that image quality does not deteriorate. Therefore, when looking at the entire image data, it is possible to keep transmission cost or medium cost low while maintaining high image quality.

According to a second aspect of the present invention, in the color image compression apparatus according to the first aspect, the reversible compression method divides a gradation color image into RGB planes, and performs primary conversion on element data in each plane. Calculating a difference, further calculating a secondary difference with respect to the primary difference, and when the secondary difference is not zero, using the secondary difference, performing variable length coding on each plane; Are continuously zero, each plane is variable-length coded using the number of consecutive zeros. In this way, a gradation image is subjected to variable-length coding by applying the difference method, thereby providing a color image compression method that improves the compression ratio and does not degrade the image quality.

According to a third aspect of the present invention, in the color image compression apparatus according to the first or second aspect, the regularity detecting means determines that all secondary differences between the adjacent data are "0". It is configured to detect. By doing so, as shown in the first and second patterns of FIG.
The secondary differences are all “0”. In this case, the continuous number of secondary differences may be counted by the "color image compression method" and the count number may be compressed, so that the compression ratio can be increased, and the transmission cost or the medium cost is suppressed. There is.

According to a fourth aspect of the present invention, in the color image compressing apparatus according to the first or second aspect, the regularity detecting means determines that the absolute value of the secondary difference between the adjacent data is all “1” or less. Is detected.
In this way, for example, as shown in the third pattern of FIG. 1, the secondary difference is “1, −1, 1” or “−1,
1, -1 "(that is, all the absolute values are" 1 "or less).
In this case, since the secondary difference is compressed based on the codebook by the “color image compression method”, it is possible to increase the compression rate and to suppress the transmission cost or the medium cost.

According to a fifth aspect of the present invention, when image data present on the host device is displayed on another display device via a transmission line or a medium, the image data is compressed on the host device side, In a color image compression method designed to be expanded on a display device, the image data is converted to R, G, B
, Calculating a primary difference between adjacent data in each of the divided planes, calculating a secondary difference between adjacent data of the calculated primary difference, Detecting whether there is regularity in between, and if the detected data has regularity, the image data is compressed by a lossless compression method; if the detected data does not have regularity, Compressing the image data by an irreversible compression method.

In this way, as in the case of the first aspect, when there is regularity, the lossless compression method ("color image compression method") for the gradation system is adopted, so that the image quality is not degraded. In addition, transmission costs or medium costs can be reduced. Conversely, when there is no regularity, an irreversible compression method with a high compression ratio (for example, the well-established JPEG
Method), the image quality does not deteriorate. Therefore, when looking at the entire image data, it is possible to keep transmission cost or medium cost low while maintaining high image quality.

According to a sixth aspect of the present invention, in the color image compression method according to the fifth aspect, the step of detecting the presence / absence of the regularity is such that all the secondary differences between the adjacent data are “0”.
Is detected. With this configuration, as in the case of the second aspect, the continuous number of secondary differences is counted by the “color image compression method”, and the count number may be compressed, so that the compression ratio can be increased. This has the effect of reducing transmission costs or medium costs.

According to a seventh aspect of the present invention, in the color image compression method according to the fifth aspect, the step of detecting the presence / absence of the regularity is performed when the absolute value of the secondary difference between the adjacent data is all “1” or less. Detect that there is. With this configuration, as in the case of the third aspect, the “color image compression method”
, The secondary difference is compressed based on the codebook, so that the compression ratio can be increased and the transmission cost or the medium cost can be suppressed.

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A color image compression apparatus and method according to the present invention will be described below with reference to the illustrated embodiments. (1) Outline of the present invention Prior to the description of the present embodiment, the outline of the present invention will be described.
The present invention solves the above-mentioned problem by appropriately selecting an irreversible compression method such as a JPEG method and a lossless compression method specialized in a gradation system (for example, a “color image compression method” described later). This is an image application type compression method for selecting a compression method for each area (processing block) of image data.

The color image of the gradation system is represented by R,
When divided into G and B elements, the characteristic is that the value gradually increases and decreases in each element. Therefore, first, the image is divided into R, G, and B planes, and each divided plane is focused on. As shown in FIG. 1, a primary difference between adjacent data in each of the divided planes, a previous primary difference, and a currently processed secondary difference are obtained. As shown in the figure, a gradation pattern includes a first pattern in which data increases and decreases one by one, a second pattern in which data increases and decreases by N (natural number), and a rule that data is N and N + 1. There is a third pattern in which the frequency is switched and increases / decreases. On the other hand, in the case of a normal image, regularity is not recognized in both the primary difference and the secondary difference as in the fourth pattern.

The present invention focuses on these characteristics and selects a compression method by the following algorithm. In the processing block, when the values of the secondary differences of the respective planes are equal, if the values of the secondary differences are all “0”, a lossless compression method for a gradation system (for example, a “color image Compression method)). Under the same conditions as above,
The adjacent secondary differences in the processing block are "1, -1,
Also when there is a sequence of "1" or "-1, 1, -1" (that is, when the absolute values of the secondary differences are all "1" or less), the gradation-based lossless compression method is adopted.
Here, when the secondary difference is “0”, and when “1, −1,1” or “−1,1, −1” (that is, the absolute value of the secondary difference is “1” or less) If there is a line,
It is called "regular". In other cases (when there is no “regularity”), the lossy compression method (for example, JP
EG method).

(2) Description of "Color Image Compression Method" As the "color image compression method", for example, a color image compression method previously filed by the present applicant as Japanese Patent Application No. 2002-100553 can be suitably used. . The conventional compression method of a gradation image compresses the primary difference value or compresses the original image data itself when the secondary difference is not zero, so that the compression ratio cannot be improved. There was such a problem. Japanese Patent Application 2002-1
The “color image compression method” according to No. 00553 is intended to solve the above-mentioned problem. The compression rate is improved by applying a variable-length coding to a gradation image by applying a difference method. This is a color image compression method that does not degrade image quality.

An embodiment of a "color image compression system" according to Japanese Patent Application No. 2002-100553 will be described. FIG.
FIG. 5 is a flowchart of an embodiment of the “color image compression method”, FIG. 5 is a codebook used in the embodiment, (a) is a data compression codebook, and (b) is a run-length compression codebook. It is. FIG. 6 is a block diagram of an image compression device that implements the “color image compression method”.

In FIG. 4, first, a gradation color image is divided into RGB planes (step S5).
1). Next, image data is obtained from the divided planes (step S52). In obtaining this data, an arbitrary one byte is obtained from the elements of the image. Next, it is determined whether or not the acquired image data is the first byte, that is, the first byte (step S53). here,
If the acquired image data is the first byte, data compression is performed on the image data (step S54).

This data compression is performed based on the data compression codebook shown in FIG. In the figure, the codebook for data compression includes a total number of bits, an identification code, a code length, and a data value range. A code and a code length are set. The total number of bits indicates the total number of bits of the identification code and the data value. The closer the data value to be compressed is to zero, the smaller the size can be. The length of the code is the number of data bits when compressing the data value, and the identification code is bit data added to data indicating the length of the code.

The range of the data value is (0), (-1, -1) depending on the data value (an integer from -255 to 255).
1), (-3, -2, 2, 3), (-7 to -4, 4 to
7), (-15 to -8, 8 to 15), (31 to -1)
6, 16 to 31), (−63 to −32, 32 to −6)
3), (-127 to -64, 64-127) and (-2)
55-128, 128-255). The data compression is performed by combining the identification code of “data value range” corresponding to the value of the image data of the first byte and the data of the first byte represented by the number of bits corresponding to the length of the code.

For example, if the data of the first byte is "5", the identification code is "11110" in binary from the "range of data values". In addition, since the code length is “3”, the data “5” of the first byte is “101” when represented by a binary number. This "11110" and "1
01 "and output in the form of" 11110101 ".

Next, it is determined whether or not the data is the last data (step S66). If the data is continued, the process returns to step S52 to acquire the next data. Then, in step S53 again, it is determined whether or not the acquired data is the first byte. Since this data is the second byte, the process proceeds to step S55, and it is determined whether or not the data is the second byte (step S55). Here, since the acquired data is the second byte, the process proceeds to step S56, where the primary difference between the first byte and the second byte is calculated (step S5).
6) Subsequently, the calculated primary difference value is compressed (step S57). The method of compressing the primary difference value is performed in the same manner as the data compression in step S54.

Next, it is determined whether or not the data is the last data (step S66). If data is continued, the process returns to step S52 to acquire the next data. And 3
After the byte, data acquisition (step S52) is followed by step S58 via steps S53 and S55. Then, a primary difference between the previously acquired data and the currently acquired data is obtained (step S58), and subsequently, a secondary difference between the previously acquired primary difference and the currently acquired primary difference is obtained (step S59).

Next, it is determined whether or not the secondary difference obtained in step S59 is zero (step S60). When the secondary difference is zero, one run length count is added (step S61). Proceed to S66. On the other hand, when the secondary difference is not zero, it is determined whether or not the run length count is zero (step S62). Then, step S62
When the run length count is zero, the process proceeds to step S65, then compresses the secondary difference value obtained in step S59 (step S65), and determines whether the data is the last data (step S66). If the data continues, the process returns to step S52 to acquire the next data. This method of compressing the secondary difference value is performed in the same manner as the data compression in step S54.

On the other hand, if the run length count is not zero in step S62, the run length count is compressed (step S63). The compression of the run length count is performed based on the code book of the run length compression shown in FIG. In FIG. 2B, the code book of the run-length compression includes a total number of bits, an identification code, a code length, and a data value range.
The total number of bits, the identification code, and the length of the code are set. The total bit number and the code length are the same as the total bit number and the code length.

The range of the data value is the data value (1 to 25).
(Integer up to 5), (1), (2, 3), (4 to
7), (8-15), (16-31), (32-6)
3), (64-127) and (128-255). Run-length compression is performed by combining an identification code of "data value range" according to the value of the run-length count in the first byte with the data of the run-length count indicated by the number of bits corresponding to the length of the code. Do. For example, when the run length count is "5", the recognition code is "01110" in binary from the "range of data values".

When the run length count is "5",
Although expressed as a binary number, it is "101". Unlike a normal value, the run length count value has no negative value.
Since 1 is always set in the most significant bit, the specification is such that the most significant bit 1 is added on the decompression side, and the most significant bit 1 is omitted and represented as “01”. Therefore, the length of the code is “2”, and data of one bit is reduced. The combination of “01110” and “01” is output in the form of “0111001”.

Next, the run length count is initialized to zero (step S64), and the flow advances to step 65 to compress the secondary difference value obtained in step S59 (step S6).
5) Then, it is determined whether or not the data is the last data (step S66).
Returning to step 52, the next data is acquired. In step S66, it is checked whether the data is the last data, and the process returns to step S52 until the last data is reached, and the above processing is repeated. Then, when the last data is obtained, step S6
The process proceeds to step S7, where it is determined whether or not the run count is zero as in step S62 (step S67). When the run count is zero, the process ends.

On the other hand, if the run count is not zero at step S67, the run count is compressed as in step S63 (step S63).
68) Then, similarly to step S64, the run count is initialized to zero (step S69), and the process ends.

Next, an image compression apparatus for performing the above-described color image compression method will be described with reference to FIG. In FIG. 1, an image compression device 100 includes an input device 110 for inputting a target image, a storage device 140 for storing input images and output compressed data, and a data processing device 130 that operates under program control. ing. The storage device 140 includes an input image data buffer area 141 and an output data buffer area 142, and temporarily stores input and output data. The data processing device 13
0 is the difference means 131 and the rungence addition means 132
And a data compression unit 133 for compressing the input image and outputting the compressed image to the output device 120.

As described above, according to the color image compression method of the present embodiment, the characteristics of the gradation color image, that is, the secondary difference values of the image data are almost always zero, 1, and -1. Utilizing this fact, when zeros are consecutive as the secondary difference value, the number of consecutive zeros is counted and the counted number is compressed, so that the compression ratio can be greatly improved. Further, since the number of consecutive zeros is compressed by the run count, the compression efficiency can be improved as the number of consecutive zeros increases.

Even when the secondary difference value of the image is other than zero, since the secondary difference value is compressed and the data of the original image is not compressed, it is almost always necessary to compress 1 or -1. That is, as the value to be compressed is closer to zero, the total number of bits can be reduced, and the image compression efficiency can be improved.
For example, to compress the third pattern shown in FIG.
Since the compression of the primary difference requires 74 bits, while the compression of the secondary difference requires only 42 bits, the compression ratio can be greatly improved.

Further, there is a method of compressing data obtained first from each plane based on a data compression codebook divided into ranges of data values. By doing so, complicated processing is not performed. Also, the data can be easily compressed. Further, there is a method of compressing the secondary difference based on the codebook. By doing so, the secondary difference of the gradation color image, that is, zero, -1, 1 can be easily and efficiently obtained. Can be compressed. Also, even when the secondary difference of the image is not zero, the secondary difference value is compressed,
It is good to reproduce the data of the original image from this secondary difference value,
By doing so, each plane can be reversibly encoded in a variable length, and the problem that the image quality is reduced can be avoided.

This "color image compression method" is not limited to gradation type color images, but
It is a matter of course that the above-described compression effect can be obtained for an image in which the image data continuously increases and decreases, that is, for an image in which the secondary difference is a value close to zero.

As described above, according to the "color image compression system", the total number of bits of the compression can be reduced by directly compressing the value of the secondary difference in the gradation image, and the compression of the image can be reduced. Efficiency can be greatly improved. Further, since the image can be compressed so that the image can be reversibly reproduced, the image is not deteriorated by the compression, and the deterioration of the image quality can be prevented.

(3) Embodiment of the Present Invention FIG. 2 is a block diagram of a color image compression apparatus according to this embodiment. As shown in FIG. 2, the color image compression device KA
An input device 10 for inputting image data to be processed;
A program-controlled data processing device 20 for performing various processes on the image data, and a storage device 30 for storing various data
And an output device 40 for decompressing and outputting the compressed data.

The data processing device 20 comprises an RGB plane dividing means 21, a primary difference calculating means 22, a secondary difference calculating means 23, a regularity detecting means 24, a compression method selecting means 25, an irreversible compressing means 26 And the reversible compression means 27
And The RGB plane dividing means 21 divides the image data to be processed into R, G, and B planes. The primary difference calculating means 22 calculates a primary difference between adjacent data in each plane divided by the RGB plane dividing means 21 (see FIG. 1). The secondary difference calculation means 23 calculates a secondary difference between adjacent data of the primary difference calculated by the primary difference calculation means 22.

The regularity detecting means 24 detects the regularity between the adjacent data calculated by the secondary difference calculating means 23. As shown in FIG. 1, the compression method selection unit 25 performs a case where the data detected by the regularity detection unit 24 has a regularity (for example, a case where all the secondary differences are “0”).
Then, the image data is compressed by a lossless compression method, and when the detected data has no regularity, the image data is compressed by an irreversible compression method. As the irreversible compression means 26, a JPEG method having a high compression ratio (several tenths) and capable of arbitrarily adjusting the compression ratio is used.
As the reversible compression means 27, the above-mentioned "color image compression method" is used.

That is, if the detection data of the secondary difference has "regularity", the compression method selection means 25 determines whether the reversible compression method ("color image compression method") having a high compression rate specialized for the gradation system is used. To reduce transmission or media costs. Conversely, when the detection data of the secondary difference is “irregular”, an irreversible compression method with a high compression ratio (for example, JPEG method) is adopted. In this manner, when the entire image data (gradation-based data) including both regular data and irregular data is viewed, the image quality can be maintained high even if the compression ratio is increased. Transmission cost or medium cost can be reduced.

The storage device 30 includes an input image data buffer area 31 for storing input image data, an output compressed data buffer area 32 for storing output compressed data, and a compression method determination used in compression determination processing (described later). And a work area 33 for processing. The output device 40 includes a compressed data decompression unit 41 that decodes and decompresses the data that has been compressed and transmitted by the data processing device 20, and displays the decompressed data on a screen (display device) or the like.

Next, the operation of this embodiment will be described with reference to the flowchart shown in FIG. Here, R,
The processing of a 24-bit color image in which each of G and B data is composed of 1 byte (8 bits) will be described as an example. After dividing into R, G, and B planes in advance, processing according to the flowchart shown in FIG. 3 is performed.

In FIG. 3, terms such as count and seq_c have the following meanings, respectively. count: A counter seq_ indicating the byte position of the data to be processed in each plane.
c: Third pattern detection counter R [x], G [x], B [x]: x-th data of each plane Diff1_R [x], Diff1_G, [x], Diff1_B [x]: x-th Holding array of primary difference data Diff2_R [x], Diff2_G, [x], Diff2_B [x]: holding array of x-th secondary difference data These data are sent to the compression method determination work 33 of the storage device 30. Secured.

The processing will be described below in the order of processing in the flowchart shown in FIG. Step S1: Initialize a counter (count, seq_c). Step S2: The primary difference between the first byte and the 0th byte of each plane is calculated, and Diff1_R [1], Diff1_G [1], Di1
ff1_B [1] is held, and count is incremented by one. Step S3: The primary difference between the (count + 1) th byte and the (count) th byte of each plane is calculated, and Diff1_R [count], Diff1_G [co
unt], Diff1_B [count]. Step S4: In each plane, a secondary difference is obtained from the two primary difference data of the count and count-1 and is stored in the secondary difference data holding array.

Step S5: If the secondary differences of the respective planes are equal (for example, the secondary differences of R, G, B are
If all are “0”, the process proceeds to step S6. Otherwise, the process proceeds to step S12 to initialize the counter seq_c. Step S6: If the absolute value of the secondary difference is smaller than 1, go to step S7. Otherwise, go to step S12. Step S7: If the secondary difference is “0”, it is determined to be a gradation system and the process ends (step S20). That is,
The compression ratio is increased by performing reversible compression specialized for gradation systems (for example, using a “color image compression method”), and transmission costs or medium costs are suppressed. Otherwise, go to step S8.

Step S8: If the third pattern detection counter seq_c is 0, the flow advances to step S10 to increment the counter seq_c by one. Otherwise, go to step S9. Step S9: If the sum with the immediately preceding secondary difference value is 0 (for example, secondary difference “1” + “− 1” = 0), step S10 is performed to continue the third pattern detection process. Proceed to. Otherwise, go to step S12. Step S10: Third pattern detection counter seq_c
Is incremented by 1 and the process proceeds to step S11. Step S11: If the third pattern detection counter
If seq_c is 2 or more, the process is terminated assuming that the third pattern has been detected (step S20). Otherwise, the process proceeds to step S13.

Step S12: Counter for pattern detection
Reset seq_c. (Initialized to 0) Step S13: The byte position counter count is incremented by one. Step S14: If the byte position counter count exceeds the processing block length (24 bits in this case),
It is determined that the pattern is the fourth pattern, and the process ends (step S21).
Otherwise, the process proceeds to step S3 to continue the processing.

Step S21: A gradation pattern is detected, and the processing ends. The process proceeds to a reversible compression process (for example, “color image compression method”). Step S21: end without detecting a gradation pattern. Proceed to irreversible compression processing (for example, JPEG method). As described above, after selecting the compression method based on the presence or absence of the regularity of the secondary difference, the lossless compression method or the irreversible compression method is performed, so that compression processing with appropriate quality can be performed.

[0050]

As described above, according to the present invention, by appropriately selecting irreversible compression and lossless compression, it is possible to suppress the transmission cost or the medium cost and to achieve the color image compression which ensures the quality at the time of decompression. It becomes possible.

[Brief description of the drawings]

FIG. 1 is a diagram showing that data in each element of a gradation-based color image has four increase / decrease patterns.

FIG. 2 is a block diagram of a color image compression apparatus to which an embodiment of the present invention is applied.

FIG. 3 is a flowchart illustrating the processing of the color image compression device of the present invention.

FIG. 4 is a flowchart illustrating a color image compression method of a “color image compression method”.

5A and 5B are codebooks used in the embodiment of the “color image compression method”, wherein FIG. 5A is a codebook for data compression, and FIG. 5B is a codebook for run-length compression.

FIG. 6 is a block diagram of an image compression apparatus that performs a color image compression method of a “color image compression method”.

[Explanation of symbols]

KA color image compression apparatus 10 input apparatus 20 data processing apparatus 21 RGB plane division means 22 primary difference calculation means 23 secondary difference calculation means 24 regularity detection means 25 compression method selection means 26 irreversible compression means 27 reversible compression means 30 storage device 31 Input image data buffer area 32 Output compressed data buffer area 33 Compression method determination processing work 40 Output device 41 Compressed data expansion means 100 Image compression device 110 that implements “color image compression method” 110 Input device 120 Output device 130 Data processing device 131 Difference means 132 Run length addition means 133 Data compression means 140 Storage device 141 Input compressed data buffer area 142 Output compressed data buffer area

   ────────────────────────────────────────────────── ─── Continuation of front page    F term (reference) 5C057 AA11 BA13 DC11 EA01 EL01                       EM00                 5C059 MA00 MA45 ME01 ME05 PP01                       PP15 UA02                 5C078 AA09 BA22 BA32 CA02 CA21                       DA01                 5J064 AA01 BA09 BB01 BB05 BC25                       BD03

Claims (7)

[Claims] 1. An image data residing on a host device,
A color image compression device configured to compress the image data on the host device side and expand the image data on the display device when displaying the image data on another display device via a transmission path or a medium; R divided into G and B planes
GB plane dividing means, primary difference calculating means for calculating a primary difference between adjacent data in each plane divided by the RGB plane dividing means, and calculating a secondary difference between adjacent data of the primary difference calculated by the primary difference calculating means Secondary difference calculating means, regularity detecting means for detecting whether there is regularity between the adjacent data calculated by the secondary difference calculating means, and a rule for the data detected by the regularity detecting means. If there is a characteristic, the image data is compressed by a lossless compression method, and if the detected data has no regularity, a compression method selection unit that selects to compress the image data by an irreversible compression method. A color image compression device comprising: 2. The color image compression apparatus according to claim 1, wherein the lossless compression method divides a gradation color image into RGB planes, calculates a first-order difference with respect to element data in each plane, Calculate the secondary difference for the primary difference, and when the secondary difference is not zero, use the secondary difference to perform variable length coding on each plane, and further, the secondary difference is continuously zero. A color image compression system that employs the number of consecutive zeros to perform variable-length encoding on each plane using a color image compression method. 3. The color image compression device according to claim 1, wherein said regularity detecting means is means for detecting that all secondary differences of said adjacent data are “0”. A color image compression device characterized by the above-mentioned. 4. The color image compression apparatus according to claim 1, wherein said regularity detection means determines that all absolute values of secondary differences between said adjacent data are less than or equal to an absolute value “1”. A color image compression device, which is a means for detecting. 5. An image data existing on a host device,
A color image compression method for compressing the image data on the host device side and expanding the image data on the display device when displaying the image data on another display device via a transmission path or a medium; Dividing the plane into G and B planes, calculating a primary difference between adjacent data in each of the divided planes, calculating a secondary difference between adjacent data of the calculated primary differences, Detecting whether there is regularity between adjacent data; and, if the detected data has regularity, compressing the image data by a lossless compression method, and the detected data has no regularity. A step of compressing the image data by an irreversible compression method. 6. The color image compression method according to claim 5, wherein the step of detecting the presence or absence of the regularity is a step of detecting that all the secondary differences of the adjacent data are “0”. Characteristic color image compression method. 7. The color image compression method according to claim 5, wherein the step of detecting the presence or absence of the regularity includes the step of detecting that the absolute values of the secondary differences between the adjacent data are all “1” or less. A color image compression method, characterized in that: