CN113256747B

CN113256747B - Bitmap index compression method, bitmap index decompression equipment and bitmap index medium

Info

Publication number: CN113256747B
Application number: CN202110380599.6A
Authority: CN
Inventors: 陈成秋; 李宗宇; 邱文庆; 蓝涛
Original assignee: Fujian Centerm Information Co Ltd
Current assignee: Fujian Centerm Information Co Ltd
Priority date: 2021-04-09
Filing date: 2021-04-09
Publication date: 2023-10-20
Anticipated expiration: 2041-04-09
Also published as: CN113256747A

Abstract

The application provides a bitmap index compression method, a decompression method, equipment and a medium, wherein the compression method comprises the following steps: establishing an index table, determining the corresponding relation between color values and index values, enabling the color values to be corresponding to the index values from small to large according to the occurrence frequency, and representing the color values by using codes from short to long of variable word length codes; and replacing color values in the image with the variable word length coding sequence according to the created index table to obtain picture coding data, and storing the index table data and the picture coding data as compressed data, wherein the index table data comprises table lengths and color values. The decompression method comprises the following steps: acquiring the index table data and the picture coding data; sequentially reading the picture coding data; and sequentially inquiring the index table data, and recovering each coding value in the picture coding data into a corresponding color value in the index table. The application can realize lossless compression of bitmaps with various colors, reduce memory occupation and improve bitmap compression and decompression efficiency.

Description

Bitmap index compression method, bitmap index decompression equipment and bitmap index medium

Technical Field

The present application relates to the field of image compression, and in particular, to a bitmap index compression method, a bitmap index decompression device, and a bitmap index decompression medium.

Background

Among lossless compression algorithms used for bitmap compression, there are often RLE (run-length encoding), huffman (Huffman coding), LZ77, and the like. Of these, huffman is currently the most widely used Variable Length Coding (VLC).

In the existing bitmap compression, an index is used to replace a color value to compress an image, in most application scenes, huffman is applied to the occasion that the number of coded objects is not more than 256, if the number of coded objects is too large (more than 256), the compression effect is poor, but because the probability of adopting the number of colors of a single image is more than 256, in order to achieve a better compression effect, the common solution is to cut down the number of codes, namely the number of colors to a certain extent. For example, colors that are used less frequently in the image are replaced with similar color values. However, this solution has the disadvantage that the compression is lossy, i.e. the compressed image is not identical to the original image.

Disclosure of Invention

The application aims to solve the technical problem of providing a bitmap index compression method, a bitmap index decompression method, bitmap index decompression equipment and a bitmap index decompression medium, so that lossless compression is realized, memory occupation is reduced, and bitmap compression and decompression efficiency is improved.

In a first aspect, the present application provides a bitmap index compression method, the method including:

step 10, establishing an index table, determining the corresponding relation between color values and index values, and corresponding the color values to the index values from small to large according to the occurrence frequency, wherein the index values are represented by variable word length codes from small to large;

and step 20, replacing color values in the image with the variable word length coding sequence according to the created index table to obtain picture coding data, and storing the index table data and the picture coding data as compressed data, wherein the index table data comprises table lengths and color values.

Further, the step 10 further includes:

traversing the color values in the bitmap in sequence, recording the occurrence frequency of each color value, and filling the color values into an index table;

arranging all color values from big to small according to the occurrence frequency;

and filling the sequenced color values with corresponding index values, wherein the index values are sequenced from small to large and are sequentially 0,1,2,3, … and M.

Further, the step 10 further includes optimizing an index table, where the optimized index table includes a single index table and multiple index tables;

recording all color values with the occurrence frequency of 1 in the single index table, and arranging according to the occurrence sequence of the traversal pixel values, wherein the index values of the color values in all the single index table are the same;

the color values with the occurrence frequency of 1 are expressed by a virtual color value RGBx, and the number of the color values with the occurrence frequency of 1 is accumulated to be used as the occurrence frequency of the virtual color value RGBx;

and in the multiple index table, all color value data with the occurrence frequency greater than 1, including the virtual color value data, are arranged according to the occurrence frequency of the color values from large to small, the occurrence frequencies are the same, and are arranged according to the sequence of occurrence when traversing RGB, index values are correspondingly established for the arranged color values, the index values are arranged from small to large, 0,1,2,3, … and K are sequentially filled in the index table from 0, and the index values corresponding to the virtual color values RGBx are filled in the single index table to be used as the index values of the color values with the occurrence frequency of 1.

Further, the virtual color value RGBx is replaced in advance with any one color value in the single index table.

Further, the variable word length code is a custom variable word length code cv, and the variable word length code cv has the structure:

a head c+a tail v;

the head part c is used for indicating the occupied number of the tail part v, the bit number n=c+1 of the tail part, the cv forms a complete coded value, and the number L of the cv code values which can be represented by the variable word length coded cv at most is sigma 2 ¹ +2 ² +...+2 ⁿ And the index values arranged from small to large are corresponding to the cv code values arranged from small to large, so that the bitmap color index values are encoded.

Further, the step 10 further includes compressing the bitmap with RLE.

In a second aspect, the present application provides a bitmap index decompression method, the method comprising:

acquiring index table data and picture coding data in the method according to the first aspect;

sequentially reading the picture coding data;

and sequentially inquiring the index table data, and recovering each coding value in the picture coding data into a corresponding color value in the index table.

In a third aspect, the application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of the first aspect when executing the program.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the method of the first aspect.

One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:

1. the encoding and decoding processes are simple, the speed is high, the image data only need to be traversed twice in the compression process, the image data are respectively used for establishing an index table and color value coding substitution, and the encoding can be restored to the color value only by looking up a table in the decompression process;

2. the cv coding adopted by the application has simple structure and better compression effect, compared with Huffman coding, the method is a definite coding, namely, the cv coding value and the index value are in a predetermined corresponding relation, while Huffman needs to create a binary tree according to the occurrence probability of the color value, and the corresponding relation between the coding and the index value can be clearly coded after VLC coding is generated according to the tree;

3. basically without consuming memory, a cv code lookup table can be read to obtain a color value and then a decoding file is written once, so that only one coded memory is needed for decompression under the limit condition, and the small embedded system with limited resources can be satisfied;

4. the vc code of the application can be used in combination with other algorithms to perform secondary compression so as to achieve better compression effect and flexible application.

The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.

Drawings

The application will be further described with reference to examples of embodiments with reference to the accompanying drawings.

FIG. 1 is a flowchart illustrating a bitmap index compression method according to a first embodiment of the present application;

FIG. 2 is a flowchart illustrating a bitmap index decompression method according to a second embodiment of the present application;

fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present application;

fig. 4 is a schematic structural diagram of a medium in a fourth embodiment of the present application.

Detailed Description

The embodiment of the application provides a bitmap index compression method, a decompression method, equipment and a medium, which are used for solving the problems that the existing variable word length coding cannot realize lossless compression and high-definition reduction of bitmaps with various colors (more than 256), realizing lossless compression, reducing memory occupation, improving bitmap compression and decompression efficiency and obtaining better compression effect.

The overall structural design of the compression in the present application is shown in table a below:

table A

In the process of creating the index table, the index value, the color value and the code value are all in one-to-one correspondence in sequence, and only the color value and the table length of the index table are required to be recorded and stored. For the optimized index table (a plurality of index tables and a single index table), the plurality of index tables are repeatedly arranged according to the number of times of the repeated occurrence of the color values from large to small, namely, the more the occurrence number of times is, the smaller the index values are, after the sequencing, only the length and the color data of the table are required to be recorded, the single index table is arranged according to the sequence of the occurrence when the RGB data are traversed, the color values in the table correspond to the same index, and only the length and the color data of the table are required to be recorded. The index table data storage space is reduced.

The picture coding data is to store corresponding coding data according to the traversing sequence of the color data of each pixel point in the picture, and arrange the coding data in a compact sequence (the multiple part of the data part is automatically filled with multiple of 8 if the data part is less than 8, namely the filling is aligned according to bytes). All that needs to be recorded is the total bit length of the picture coding data and the coding value of each pixel point.

In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.

Example 1

The present embodiment provides a bitmap index compression method, as shown in fig. 1, including:

step 10, establishing an index table, determining the corresponding relation between color values and index values, and corresponding the color values to the index values from small to large according to the occurrence frequency, wherein the index values are represented by variable word length codes from small to large; namely, the variable word length coding corresponds to the index value from small to large in value;

In this embodiment, the step 10 further includes:

For example, when traversing bitmap data, such as RGB values of pixels, table 1 is generated:

TABLE 1

Pixel color value	Number of occurrences
		RGBa ₁	CNTa ₁
RGBa ₂	CNTa ₂
		...	...
RGBa _M	CNTa _M

The pixel values are ordered according to the number of occurrences from large to small, and the ordered table is recorded as table 2:

TABLE 2

Pixel color value	Number of occurrences
		RGBb ₁	CNTb ₁
RGBb ₂	CNTb ₂
		...	...
RGBb _M	CNTb _M

The index values corresponding to the pixel values are arranged from small to large to obtain table 3:

TABLE 3 Table 3

Pixel color value	Index value
		RGBb ₁	0
RGBb ₂	1
		...	...
RGBb _M	M

In this embodiment, the bitmap data overall structure is represented as color data before compression, and is represented as an index table and index data after compression. Storing index data according to the traversing sequence of the color data, and compactly arranging indexes according to bits. The total bit length of the index data needs to be recorded, and if the multiple part of the data part is less than 8, the multiple part is automatically filled with the multiple of 8, namely the data part is filled with the data part aligned by bytes.

Preferably, the step 10 further includes optimizing an index table, where the optimized index table includes a single index table and multiple index tables;

For example, color values having the number of occurrences of 1 are recorded in the single index table 4 (the pixel values in the table are required to be arranged according to the order of occurrence):

TABLE 4 Table 4

Pixel color value	Number of occurrences
		RGBd ₁	1
RGBd ₂	1
		...	1
RGBd _k	1

Color values whose number of occurrences is not 1 are recorded in the multiple index table 5:

TABLE 5

Pixel color value	Number of occurrences
		RGBc ₁	CNTc ₁
RGBc ₂	CNTc ₂
		...	...
RGBc _K-1	CNTc _K-1

Uniformly recording all pixel values with the occurrence number of 1 as virtual color value data RGB _x The number is recorded as CNT _x Introduction ofThe multiple index table 6 is obtained from the multiple index table 5:

TABLE 6

The multiple index table 7 is obtained after the arrangement from big to small according to the occurrence times:

TABLE 7

Pixel color value	Number of occurrences	Index value
			RGBc ₁	CNTc ₁	0
RGBc ₂	CNTc ₂	1
			...	...	...
RGB _x	CNT _x	x
			...	...	...
RGBc _K	CNTc _K	K

That is, the maximum value of the optimized index value corresponds to a size obtained by subtracting the number of pixels appearing only 1 time. Since the index value adopts a variable length representation method, the smaller the index maximum value is, the fewer the number of bits needed for representation is, and the better the compression effect is naturally. Thus, introducing the above optimization may reduce the index maximum.

The optimized single index table (shown in the following table 8) and the optimized multiple index table (shown in the following table 9) are obtained after the optimization:

TABLE 8

Pixel color value	Index value
		RGBc ₁	0
RGBc ₂	1
		...	...
RGB _x	x
		...	...
RGBc _K	K

TABLE 9

The storage sequence of the color values in the table illustrates the index values corresponding to the colors, and the index values and the cv codes are in a fixed corresponding relation, so that the corresponding relation between the color values and the coded values is already determined in the process of constructing the table, and therefore, when the index table data is finally stored, only the color values are needed to be stored, the index values and the coded values corresponding to each color value are not needed to be stored, and the occupied space of the index table data is greatly reduced. For the multi-time index table, only the length (i.e. the number of the color values) and the color data of the table are needed to be recorded, namely 'length+color 1+color 2+color 3+ … …', the corresponding index values are automatically counted from 0, namely the RGB values in the table sequentially correspond to 0, 1. For the single index table, all color values correspond to the same index value x, and all color values are pointed to one virtual color value, the virtual color value RGBx is replaced by any one color value in the single index table in advance, and the first color value in the single index table is generally adopted as the virtual color value to be filled into the multiple index tables (for example, RGBx in table 8 is equal to RGBd in table 9) ₁ ). Therefore, the single index table only needs to record the table length (i.e. the number of the color values) and the color data. For adopting an optimized modeThe structure of the resulting final index table data is shown in table 10 below.

Table 10

Multiple table length

RGBc1～RGBc _K

Single time table length

RGBd ₁ ～RGBd _k

Preferably, the variable word length code is a custom variable word length code cv, and the variable word length code cv has the structure:

a head c+a tail v;

the head part c is used for indicating the occupied number of the tail part v, the bit number n=c+1 of the tail part, the cv forms a complete coded value, and the number M of the cv code values which can be represented by the variable word length coded cv at most is sigma 2 ¹ +2 ² +...+2 ⁿ And the index values arranged from small to large are corresponding to the cv code values arranged from small to large, so that the bitmap color index values are encoded.

Since the value of the header c is 0-2 when the number of bits of the header c is m ^m -1, and since n=c+1, n is at most 2 ^m So that the number of variable coded cv code values is at most

Taking a 24-bit color bitmap as an example, the total colors are 2 ²⁴ I.e., 16,777,216. Therefore, not only the compression effect of the color with the large number of occurrences but also the placement of the color with the small number of occurrences are consideredThe effect is great.

When the number of bits of the header c is m, the number represented by the header c ranges from 0 to 2 ^m -1, 2 altogether ^m The number of the bits n of the tail v is 1 to 2 ^m . The index number which can be actually represented by the corresponding cv coding structure is sigma 2 ¹ +2 ² +...+2 ⁿ 。

Expressed in tabular form, the details are as follows in Table 11:

TABLE 11

Examples:

when the number of bits m of the header is 1, the bit width n of the representable tail is 2 at the maximum ¹ And each. Then the number of data that this data structure can express is Σ2 ¹ +2 ² I.e. 6, respectively binary numbers:

0b00,0b01,0b100,0b101,0b110,0b111；

the index structure sequentially shows that the numerical values are 0-5 from small to large, namely the corresponding relation is as follows in table 12:

table 12

Data structure	Structural bit width	Representative value
			0b00	2	0
0b01	2	1
			0b100	3	2
0b101	3	3
			0b110	3	4
0b111	3	5

When the number of bits m of the header is 2, the bit width n of the representable tail is 2 at the maximum ² And each. Then the number of data that this data structure can express is Σ2 ¹ +2 ² +2 ³ +2 ⁴ I.e. 30, respectively binary numbers:

0b000,0b001,0b0100,0b0101,0b0110,0b0111

0b10000,0b10001,0b10010,0b10011,0b10100,0b10101,0b10110,0b10111,

0b110000,...,0b111111；

therefore, the adoption of the cv code for coding the index value can meet the compression requirement of bitmaps with more kinds of color values, realize lossless compression, greatly reduce the coding bit width, reduce the memory and improve the compression and decompression efficiency.

In this embodiment, the present application may also use RLE to compress the bitmap before performing step 10. The compression effect can be further optimized by incorporating other algorithms into the algorithm of the present application.

Based on the same inventive concept, the application also provides a bitmap decompression method corresponding to the bitmap compression method in the first embodiment, and the details are shown in the second embodiment.

Example two

The present embodiment provides a bitmap index decompression method, as shown in fig. 2, including:

sequentially reading the picture coding data;

and sequentially inquiring the index table data, and recovering each coding value in the picture coding data into a corresponding color value in the index table. Thereby obtaining the color value of each pixel point in the picture and completing the decompression process. According to the bitmap index decompression method, each coding value in the picture coding data is traversed in sequence, and the corresponding color value can be queried from the index table according to the one-to-one correspondence of the coding values and the color value ordering, so that picture decompression is completed.

Based on the same inventive concept, the application provides an electronic device embodiment corresponding to the first embodiment, and the details of the third embodiment are shown in the specification.

Example III

The present embodiment provides an electronic device, as shown in fig. 3, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where any implementation of the first embodiment may be implemented when the processor executes the computer program.

Since the electronic device described in this embodiment is a device for implementing the method in the first embodiment of the present application, those skilled in the art will be able to understand the specific implementation of the electronic device and various modifications thereof based on the method described in the first embodiment of the present application, so how the electronic device implements the method in the embodiment of the present application will not be described in detail herein. The apparatus used to implement the methods of embodiments of the present application will be within the scope of the intended protection of the present application.

Based on the same inventive concept, the application provides a storage medium corresponding to the first embodiment, and the detail of the fourth embodiment is shown in the specification.

Example IV

The present embodiment provides a computer readable storage medium, as shown in fig. 4, on which a computer program is stored, which when executed by a processor, can implement any implementation of the first embodiment.

The technical scheme provided by the embodiment of the application has at least the following technical effects or advantages: the coding and decoding process is simple, the compression rate is high, the memory occupation is small, the coding and decoding method can be suitable for a small-sized embedded system with limited resources, the problems of blocking and the like caused by picture decompression of the small-sized embedded system are solved, the bitmap is compressed by adopting the coding algorithm, lossless compression can be realized, particularly, lossless compression can be realized by adopting the coding method aiming at bitmaps with various colors when lossless compression cannot be realized by using Huffman coding, meanwhile, similar color continuity is not required, binary trees are not required to be created, the speed is high, the influence of index quantity on the compression rate is small, the compression effect is good, in addition, the coding mode can be combined with other algorithms for secondary compression, the compression effect is improved, for example, the RLE is used for compressing the bitmap first, and then the cv coding is applied for secondary compression on color value parts, and the compression effect can be further optimized.

While specific embodiments of the application have been described above, it will be appreciated by those skilled in the art that the specific embodiments described are illustrative only and not intended to limit the scope of the application, and that equivalent modifications and variations of the application in light of the spirit of the application will be covered by the claims of the present application.

Claims

1. A bitmap index compression method is characterized in that: the method comprises the following steps:

step 10, traversing color values in the bitmap in sequence, recording the occurrence frequency of each color value, corresponding the color values to index values from small to large according to the occurrence frequency, and filling the index values into an index table, wherein the index values are represented by codes from short to long in a variable word length mode from small to large;

the variable word length code is a custom variable word length code cv, and the variable word length code cv has the structure that:

a head c+a tail v;

the head part c is used for indicating the occupied number of the tail part v, the bit number n=c+1 of the tail part, the cv forms a complete coded value, and the number L of the cv code values which can be represented by the variable word length coded cv at most is sigma 2 ¹ +2 ² +...+2 ⁿ ；

2. The bitmap index compression method according to claim 1, wherein: the step 10 further comprises:

3. The bitmap index compression method according to claim 2, wherein: the step 10 further includes optimizing an index table, wherein the optimized index table includes a single index table and a plurality of index tables;

4. A bitmap index compression method as claimed in claim 3, wherein: the virtual color value RGBx is replaced in advance with any one color value in the single index table.

5. The bitmap index compression method according to claim 1, wherein: and the index values arranged from small to large are corresponding to the cv code values arranged from small to large, so that the index values are encoded.

6. The bitmap index compression method according to claim 1, wherein: the step 10 further includes compressing the RLE bitmap with RLE.

7. A bitmap index decompression method is characterized in that: the method comprises the following steps:

obtaining the index table data and the picture coding data in the bitmap index compression method according to any one of claims 1 to 6;

sequentially reading the picture coding data;

8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 6 when the program is executed by the processor.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1 to 6.