JPH06292021A - Picture compression device - Google Patents

Abstract

PURPOSE:To obtain a picture compression device suitable for compressing a multi-color picture or the like by converting a display symbol for multi-value indication into a coded symbol so as to code the symbol for each bit plane. CONSTITUTION:Color symbols R, G, B of a picture information source 2 are inputted to a symbol conversion means 1, in which they are converted into symbols D0-D2 for coding. A coded symbol is inputted to a coding means 3, in which the symbol is coded for each bit plane comprising the bits D0-D2 and the compressed data 7 are generated and recorded in a recorder 4. Through the constitution above, the information quantity of the color expansion picture after compression is made close to the information quantity after compression of a binary picture and then the picture compressor suitable for a multi-value picture such as multi-color produced by the device of personal computer and a personal portable device and a computer is obtained.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image compression apparatus for highly efficiently encoding an image having bit planes of two or more layers, such as a multicolor image.

[0002]

2. Description of the Related Art At present, an image (a document image is simply referred to in the text) composed of a document, a figure, a table and the like created by a computer and a computer graphic (CG is referred to in the text) are electronically recorded, stored and made into a database, and are arbitrarily selected. A system for searching arbitrary images at the time has appeared. The image can be stored in a bitmap format, a format in which character codes, vector data, fonts, control data, or the like is stored. The former is advantageous in that high-speed drawing is possible because data for drawing is eliminated and data can be shared. When saving images as bitmaps, compression technology that saves more images in less memory is essential, and for practical use,
It is necessary that the device be inexpensive and that the time required for search / playback be short.

When a binary image displayed in black and white is expanded to a multivalued image, for example, a multicolor image of 8 colors, it is necessary to expand one pixel to 3 bits. For example, one bit is assigned to R, G, and B. As an encoding method for this multi-color image, a method of applying an existing encoding technique to each of the R, G, and B planes has been proposed. When compressing an image that has been color-enhanced to 8 colors, since the encoding is performed for each plane, the number of pixels is three times that of a binary image. Therefore, the amount of information after the compression of the multi-color image is remarkably increased as compared with the binary information.

[0004] In the "Electronic Society of Image Electronics, Vol. 21, No. 3," Color Facsimile for Digital Network Using Bubble Jet Recording and COSMIC Coding ", a method of coding for each plane as shown in FIG. 8 is proposed. . The encoding means 3 in FIG. 8 is a pixel prediction means 11 using a Markov model.
And the dynamic arithmetic coding means 12 are combined. To explain the Markov model, which is an important concept of this method,
FIG. 9 is used. In FIG. 9, one bit plane,
For example, focus only on the R plane. In the figure, the pixel to be encoded is x, and the pixels a, b, c around it,
d, e, and f are called reference pixels. The part (10) formed by the reference pixels is called a Markov model template. When the pixel x is encoded in the order 9 shown in the figure,
Each reference pixel has already been coded and can therefore be referenced. The state determined by the values of the six reference pixels is called Markov state (64 states) in the text.

The method using the Markov model utilizes the correlation between the coded pixel x and the reference pixel. Pixel prediction means 11
Predicts a coded pixel x from the Markov state. For example, when the reference pixels are all 0, the coded pixels are also likely to be 0. In this way, prediction is possible. When the value of a coded pixel is predicted from the Markov state and the predicted value and the value of the coded pixel match, that pixel is called a dominant pixel in the text, and if it is different from the prediction, it is called a recessive pixel. In one image, the probability that a coded pixel is inferior (= 1-dominant probability) differs depending on the Markov state, but the value is small. In this way, the coding means 3 predicts a coded pixel from the state (Markov state) of the reference pixel having a strong correlation with the coded pixel, and determines whether it is recessive or dominant. Arithmetic encoding is performed using this judgment and the probability of recessiveness determined by the Markov state. In FIG. 8, the dynamic arithmetic coding means 12 performs coding. In dynamic arithmetic coding, the probability of occurrence of this recessiveness is
It changes dynamically according to the frequency of past recessiveness.

The details of the arithmetic code and this method are described in the chapter of binary coding of "International Standard of Multimedia Coding" (Maruzen) edited by Hiroshi Yasuda.

[0007] In the method combining the above-mentioned Markov model and dynamic arithmetic coding, color correlation between planes is used,
Furthermore, the coding efficiency is improved. That is, not only the pixels in the plane (12 pixels) but also the coded pixels of other planes are referred to as reference pixels.

[0008]

The prior art multi-color image encoding system is applicable to high-priced, high-quality devices such as color copying machines and color facsimiles.

The output means is paper.

The image to be encoded is an already printed image or photograph.

On the other hand, the target image and apparatus of the present invention are as follows: The target image is a multi-valued image such as multi-color created by a computer or the like.

The compressed image is stored in a recording device and output to a display or the like.

The target device is a personal computer or a personal portable device.

From the above point of view, the conventional encoding system is not optimized for the target device and the image which are the objects of the present invention. In addition, since the number of reference pixels is large and the model template of the Markov model differs depending on the plane, the size of the hardware increases. The present invention provides the target image,
(EN) Provided is an image compression device which can obtain a high compression rate by an image encoding method suitable for the device, and an object thereof is to be an image compression device which has a simple configuration and can be realized at low cost and has a short reproduction time.

[0015]

In order to solve the above problems and achieve the object, the present invention provides a symbol conversion means for converting display symbols for multi-value display into coded symbols for coding, and coding. It is characterized in that a compression means for encoding the symbol for each bit plane is provided.

According to a second aspect of the present invention, in the image compressing apparatus configured as in the first aspect and provided with symbol converting means for converting an n-bit display symbol into an n-bit coded symbol, only the display symbol is displayed. The entropy determined by the statistical properties of the image and the encoding method of the compression means of the image formed in (3) is calculated for all the display symbols, and the display symbol indicating the background is converted into encoded symbols of all n bits 0. However, the display symbols excluding the background are ranked in descending order of entropy, and the upper n display symbols are converted into coded symbols in which only another bit is 1 and other bits are 0, and the entropy is the smallest. The display symbol is characterized by including symbol conversion means for converting an n-bit coded symbol into all 1's.

According to a third aspect of the present invention, an image compression apparatus configured as in the first aspect and including a symbol converting means for converting an n-bit display symbol into an n-bit coded symbol, an image to be compressed Occurrence frequency of the display symbol is calculated, the display symbol indicating the background is converted into a coded symbol in which all n bits are 0, and the display symbols excluding the background are ranked in descending order of occurrence frequency, and the top n display symbols are displayed. Is provided with a symbol converting means for converting into a coded symbol in which only another bit is 1 and the other bits are 0, and the display symbol having the least frequency of occurrence is converted into a coded symbol in which all n bits are 1. And

[0018]

EXAMPLES Example 1 One example of the present invention will be described by taking a map image (CG) as an example. Bitmaps that are usually bitmapped include general roads, toll roads, rivers, place names,
A color is determined by a green space, a mark, etc., and a symbol is determined for that color.

In the text, the size of the amount of information as an image of a certain symbol (color) is defined as the amount of information of an image made of only that symbol. In the image thus created, the statistical information of the image is completely different depending on the symbol, and thus the image information amount of the symbol is also greatly different. For example, the amount of information as an image of a general road is very large, and the amount of information on green areas, marks, etc. is extremely small. Further, the information amount of the image in which two different symbols are combined takes a value close to the sum (sum) of the information amounts in the images of the respective symbols. For example, the information amount of the image in which the road and the mark are combined is close to the sum of the respective information amounts. In the present invention, focusing on these two points, color symbols (described later) are converted into coded symbols (described later) that achieve the highest compression efficiency. Furthermore, the present invention provides a method of configuring the symbol converting means.

One embodiment of the present invention will be specifically described with reference to FIG. The image information source 2 is a map image whose color is expanded to 3 bits. This is, for example, R, G, B shown in FIG.
3 planes, and corresponds to R, G, and B in FIG. In the text, these (R, G, B) are color symbols. The color symbols are input to the symbol converting means 1 which is a main element of the present invention, and converted into symbols (D0, D1, D2) for encoding as shown in FIG. In the text, this is the coded symbol. Although the method of constructing the symbol converting means will be described later, the compression ratio is greatly improved. The encoded symbol is input to the encoding means 3. The encoding means 3 encodes each bit plane (FIG. 5) formed of each bit D0, D1, and D2 of the encoded symbol to generate compressed data 7. The order of encoding points may be any order as shown in FIGS. 6A, 6B, and 6C. Where (1),
(2), (3). ． ． Indicates the encoding order. Any encoding method such as MH, MR, MMR, arithmetic code, etc. may be used. In addition, the encoding method of each plane or the parameters may be different. In the present embodiment, a coding method combining the conventional Markov model and arithmetic coding is used, but the compression ratio is greatly improved by using the symbol conversion means. Further, even if the number of reference pixels is reduced (even if the color correlation between planes is not taken), the compression rate is high, so that the device can be downsized. The compressed data 7 is recorded in the recording device 4. 4 may be a communication device.

Next, a method of configuring the symbol converting means will be described. The construction method is to assign coded symbols to color symbols. As a pre-step of performing this, the information amount of the image formed by only one color symbol is obtained for all color symbols (eight in this embodiment). The image information amount of the color symbol is assumed to be an encoding system first, and based on this, an amount indicating a statistical bias of the image, here, entropy is obtained, and this is used as the information amount. The method of calculating entropy will be described at the end of Example 1.

After the completion of this previous step, symbol allocation is performed according to the following procedure.

Step 1: Rank each symbol in descending order of entropy.

In this embodiment, eight color symbols are ranked.

Procedure 2: Normally, 000 is assigned to the background having the highest entropy.

Procedure 3: Except for the background, 001, 010, 1 are assigned to the top three symbols with high entropy.
Assign 00. The order is not specified in this embodiment.

Step 4: 011 and 10 are assigned to the upper 3 symbols with high entropy, which are unassigned symbols.
Allocate 1, 110. The order is not specified in this embodiment.

Step 5: Assign 111 to the symbol with the lowest entropy.

In the above procedure, all 1's and 0's may be inverted.

In the method of constructing the symbol conversion means proposed in the present invention, color symbols having a large entropy are independently assigned to each bit plane of the coded symbols, and small color symbols are assigned across the planes. This symbol conversion is multiple (8 here).
The information amount of the composite image of the individual color symbols is determined by the color symbol with large entropy, and the fact that the image information amount of the color symbol greatly differs depending on the symbol is used. The information amount of the original image of the color expanded image is three times as large as that of the binary image, but according to the compression device using the symbol conversion of the present invention, the information amount after compression is 2 when the encoding means is the same. It approaches the amount of information after compression of the value image.

The time required for encoding by the compression device of the present invention has the same number of planes, that is, the number of encoded pixels, as compared with the time required for encoding (R, G, B) color symbols. Since the numbers are the same, it will be the same time. Further, the time required for symbol conversion can be neglected if it is realized by hardware logic, and even if it is a lookup table format using the table described in the second embodiment, it is sufficiently small.

The size of the compression device of the present invention is R, G, B.
Compared with the color symbol compression device of No. 1, only the symbol conversion unit is added, and the size thereof is small according to the above-mentioned implementation method.

Here, a method of calculating entropy when the Markov model is used will be described. FIG. 9 is used for explanation. In the text, the Markov state m determined by the value of the reference pixel is quantified by the equation 1.

M = a · 32 + b · 16 + c · 8 + d · 4 + e · 2 + f- (Equation 1) where a, b, c, d, e and f are shown in FIG. The value (1/0) of the corresponding pixel is shown. Consider a case where a certain coded pixel x is focused on in the image to be compressed (map in this embodiment). From the reference pixel value determined by this encoded pixel, Equation 1
The Markov state m is calculated by and the value (0/1) of the coded pixel x is observed at the same time. This is performed for all pixels according to the encoding order 9, for example, and the occurrence frequency a0 [m] of 0 and the occurrence frequency a1 of 1 for all 64 Markov states.
Find [m]. Further, the occurrence frequency b [m] of 64 Markov states is obtained. As a result, in a certain Markov state m, the occurrence probability Pa of 1 [1 / m] and the occurrence probability Pa of 0 are given.
[0 / m] is calculated by Equations 2 and 3. Further, the probability of occurrence Pb [m] of the Markov state is calculated by Equation 4.

Pa [0 / m] = a0 [m] / (a1 [m] + a0 [m])-(Equation 2) Pa [1 / m] = a1 [m] / (a1 [m] + a0 [m])-(Formula 3) Pb [m] = b [m] / T- (Formula 4) Here, T is the total number of pixels.

The entropy H [m] is calculated from these occurrence probabilities according to the equation (5).

[0037] Here, the base of log is 2. The method of calculating entropy is described in, for example, "Theory of Information and Code" published by Iwanami Shoten.

(Embodiment 2) In this embodiment, a document image created by a computer is color-expanded to, for example, 3 bits,
A compression device is provided. According to the compression apparatus of the present invention, the information amount of the original image which is tripled by the color expansion can be made close to the information amount after compression of the image expressed as the binary image.

This embodiment will be described in detail with reference to FIG. Normally, in a multi-color document image, characters, line drawings, ruled lines, solid paint, etc. are assigned to each color (symbol).
The amount of information of a symbol (color) as an image differs greatly depending on the symbol because the statistical properties of the image differ. For example, a character has a large amount of information, and a line drawing and a solid color are small. Utilizing this, the symbol allocation can be determined according to the procedure shown in the first embodiment.

In this embodiment, since the relationship between the color and the coded symbol is not always fixed, the correspondence relationship between the color symbol and the coded symbol of the symbol conversion means 1 (in the text, before the coding process). This is called the symbol conversion table). For that purpose, the symbol conversion means 1 is configured as a look-up table method using, for example, a RAM. The input values of this RAM table are color symbols and the output values are coding symbols. This table is implemented by the color-coded symbol table information 8 of FIG.
Can be written in the RAM.

After writing the symbol conversion table, the color symbols (R, G, B) of the image information source 2 are input to the symbol conversion means 1 and the coded symbols (D0, D1, D2) are input.
Convert to. The coded symbol is coded by the coding means 3 to generate the compressed data 7. The coding means 3 uses, for example, that shown in the first embodiment. The compressed data 7 is
For example, as shown in FIG. 7, the recording format converting unit 5 converts the color information into the recording format that is combined with the color-coded symbol information of the attribute information, and records it in the recording device 4.

Coded symbols are characters, lines, fonts,
It can also be interpreted as a symbol indicating a fill, a figure, a background, or the like. Therefore, as another effect of improving the compression rate, by changing the symbol conversion table, it is possible to reproduce a multi-color image of an arbitrary color. For example, it is possible to change only the characters to red. It is also possible to extract only arbitrary symbols and form a bitmap. For example, the bitmap can be formed only by the figures in the document. By utilizing this, it is possible to perform more intelligent document processing / output by converting a binary representation document into multiple values.

(Embodiment 3) This embodiment applies the compression device of the present invention to an image read by a color scanner or the like. This embodiment will be described with reference to FIG. In this embodiment, the image information source 2 is R, G, B from the color scanner.
Is. Further, image data from the color scanner may be stored in the frame buffer as shown in FIG.

Before performing the encoding process, the preprocessing 6 is performed using the image information source 2. This is a process in which the image information amount of the color symbol described in the first embodiment is obtained and the symbol allocation is determined accordingly. The pre-processing 6 may be the procedure shown in the first embodiment, but it takes a long calculation time, and therefore this embodiment proposes another method. This will be described later. The symbol conversion means 1 determined by the pre-processing 6 can change the symbol conversion table because the statistical property of the image to be encoded cannot be predicted (described in the second embodiment).
And After the preprocessing is completed, that is, after the symbol conversion table is written, the coding processing described below is performed.

Based on the symbol conversion table (1),
Color symbols (R, G, B) from a color scanner or frame buffer are encoded symbols (D0, D)
1, D2). The coding symbol is coding means 3
The compressed data 7 is generated. The encoding means 3 is assumed to be the one shown in the first embodiment, for example. As described in the second embodiment, the compressed data 7 is recorded in the recording format by the recording format conversion means 5 and recorded in the recording device 4.

The method of constructing the symbol conversion table proposed in this embodiment, that is, the processing contents of the preprocessing 6 will be described. Here, the image information amount of the symbol necessary for the preprocessing 6 is defined as the occurrence frequency of the symbol. That is, the coded pixels are swept in the dot order as shown in FIG. 9 (referred to as prescan in the text), and the frequency of occurrence of color symbols is counted. 1
After prescanning all the images, the frequency of occurrence of each color symbol is taken as the amount of image information. For the prescan, a color scanner may be driven for that purpose, or data stored in a frame buffer as shown in FIG. 4 may be used. Alternatively, a method may be adopted in which a plurality of suitable representative points are determined on the image and only those points are sampled to count the frequency of occurrence of color symbols.

When the occurrence frequency is known, symbol allocation is performed according to the following procedure.

Procedure 1: Arrange in order of high frequency of occurrence.

In this embodiment, the eight color symbols are ordered.

Procedure 2: Normally, 000 is assigned to the background color symbol that is most frequently generated.

Step 3: Except for the background color,
001, 010, and
Allocate 100. The order is not specified in this embodiment.

Step 4: 011, 101, and 1 are assigned to the three highest-ranked symbols whose allocation is undecided.
Assign 10. The order is not specified in this embodiment.

Step 5: Assign 111 to the symbol with the lowest occurrence frequency.

[0054]

As an advantage of storing a multi-color image in the form of a bitmap, the calculation load on the computer is reduced, high-speed drawing is possible, and data sharing is also possible. By applying the compressing device of the present invention to this multi-colored image (bit-valued), the following effects can be obtained.

The information amount of the original image of the color extended image is (number of planes) times that of the binary image, but the compression device using the symbol conversion of the present invention provides the information amount after compression. , If the encoding methods are the same, it is possible to approximate the amount of information after compression of a binary image.

Since the decoding / reproduction time of the compressed image is determined by the number of planes, that is, the number of coded pixels, it does not change in the apparatus of the present invention. Further, the processing time required for symbol conversion can be almost ignored as compared with the time required for encoding.

The hardware scale of the symbol converting means is as follows.
It is sufficiently smaller than the encoding means.

More intelligent document image processing becomes possible.

[Brief description of drawings]

FIG. 1 is a diagram showing an example of a compression device of the present invention.

FIG. 2 is a diagram showing an example when the present invention is applied to a multicolor document image.

FIG. 3 is a diagram showing an example in which the present invention is applied to a color scanner.

FIG. 4 is a diagram in which a frame buffer is provided as an image information source in FIG.

FIG. 5 is a diagram for explaining the concept of encoded symbols according to the present invention.

FIG. 6 is a diagram showing an example of an encoding dot sequence of the compression apparatus of the present invention.

FIG. 7 is a diagram showing an example of a recording format of compressed data by the compression device of the present invention.

FIG. 8 is a diagram for explaining a conventional encoding method for image compression.

FIG. 9 is a diagram for explaining an encoding method based on a Markov model.

[Explanation of symbols]

1 ... Symbol converting means which is a main element of the present invention 2 ... Multi-color (multi-value) image information source to be compressed 3 ... Encoding means for each bit plane 4 ... Compressed data Recording device 5 ... Means for converting compressed data into a recording format 6 ... Pre-processing means for determining symbol allocation of a symbol conversion table 7 ... Compressed data 8 ... Color-coded symbol information 9 ... Encoding order, 10 ... Example of model template of Markov model 11 ... Pixel prediction means using Markov model 12 is dynamic arithmetic coding means

Claims (3)

[Claims] 1. An apparatus for compressing an image having bit planes of two or more layers, symbol conversion means for converting display symbols for multilevel display into coded symbols for coding, and coded symbols for bitplanes. An image compression apparatus comprising a compression unit for encoding each image. 2. An image compression apparatus comprising the symbol conversion means configured to convert an n-bit display symbol into an n-bit coded symbol, wherein the image is formed of only the display symbol. , And the entropy determined by the encoding method of the compression means is calculated for all the display symbols, and the display symbol indicating the background is converted into an encoded symbol in which all n bits are 0, and the display symbol excluding the background is calculated. Are ranked in descending order of entropy, and the upper n display symbols are converted into coded symbols in which only one bit is 1 and the other bits are 0, and the display symbol with the smallest entropy is n bits with all 1s. An image compression apparatus comprising a symbol conversion means for converting into an encoded symbol. 3. An image compression apparatus having the symbol conversion means configured to convert an n-bit display symbol into an n-bit coded symbol, wherein the display symbol occurrence frequency is calculated in an image to be compressed. , The display symbol indicating the background is converted into a coded symbol in which all n bits are 0, the display symbols excluding the background are ranked in descending order of occurrence frequency, and the upper n display symbols are
It is characterized in that a symbol converting means is provided for converting into a coded symbol in which only another bit is 1 and the other bit is 0, and the display symbol having the least frequency of occurrence is converted into a coded symbol in which all n bits are 1. Image compression device.