JP2619758B2 - Image data compression method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for compressing image data for printing plate making, for example, and more particularly to a method for compressing multivalued image data by irreversible encoding.

[0002]

2. Description of the Related Art Since image data for printing prepress has an enormous data amount, an enormous memory capacity is required to store the image data as it is, and a large amount of time is required for data transfer. Therefore, an image data compression method of encoding image data and compressing the image data to reduce the data amount is generally used.

As a method of encoding multi-valued image data, techniques such as so-called vector quantization and orthogonal transformation are used. As the orthogonal transform, a discrete cosine transform (hereinafter, referred to as “DCT transform”) and a Hadamard transform are known. These encoding methods can compress image data at a high compression rate, but on the other hand, the image data obtained by restoring the compressed image data does not completely match the image data before compression, This is a so-called lossy encoding method. Since multi-valued image data for commercial printing has an enormous amount of data, it is one of the necessity of compression by the irreversible encoding method in particular.

By the way, commercial printing images require high image quality (for example, smooth skin, sharp edges, etc.). However, when an image is reproduced by restoring the image data compressed by the irreversible encoding method, the deterioration of the image quality becomes so small as to be visible to the naked eye, and the image may not be used as an image for commercial printing. In general, there is a tendency that the higher the compression ratio, the more the image quality of the restored image deteriorates.

As a method of increasing the compression ratio while suppressing the deterioration of the image quality of the restored image, a method described in Japanese Patent Application Laid-Open No. Sho 62-57367 is known. In this conventional method, a plurality of compression parameters for realizing a plurality of compression ratios are prepared, and an error image between the restored image and the original image corresponding to each compression ratio is displayed. Then, one error image is selected by visual judgment from a plurality of error images, and the original image is compressed using a compression parameter corresponding to the error image.

[0006]

By the way, a general image often includes a portion where image quality deterioration is conspicuous and a portion where image quality deterioration is not conspicuous. Since the outline of a portion such as a landscape or a person is not clear, the deterioration of the image quality is not conspicuous, but the deterioration of the image quality of the character portion is conspicuous because the contour is clear.

[0007] If image data of such an image is to be compressed by a conventional compression method, there is a problem that it is difficult to balance image quality and compression ratio. That is, if the image data is compressed so that the image quality of the portion where the image quality deterioration is conspicuous becomes a satisfactory level, the compression ratio becomes low. On the other hand, if the image data is compressed at a high compression rate, the image quality of a portion where the image quality deterioration is conspicuous becomes insufficient.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems in the prior art, and provides a method of compressing image data which can suppress a deterioration in image quality of a restored image and can increase a compression ratio. The purpose is to do.

[0009]

In order to solve the above-mentioned problems, the image data compression method according to the present invention comprises the steps of: (a) irreversibly encoding original image data of an image to be processed for each pixel block of a predetermined size; (B) generating decompressed image data by expanding the compressed image data; and (c) generating decompressed image data by decompressing the compressed image data. Calculating an image quality index indicating the image quality of the restored image represented by the decompressed image data for each of the pixel blocks; and (d) determining the image quality index for each of the pixel blocks. Identifying a pixel block in which the image quality index does not reach the threshold value as an image quality degraded block by comparing with a threshold value; A) displaying the processing target image while clearly indicating the image quality degraded block; (f) specifying an image region including the image quality degraded block as a low image quality region; Obtaining difference data representing a difference between original image data and the decompressed image data, and storing the difference data together with the compressed image data.

[0010]

In the low image quality area, difference data representing the difference between the original image data and the decompressed image data is stored together with the compressed image data. Therefore, when the image is restored, the decompressed image data is decompressed to obtain the decompressed image data. After that, by adding the decompressed image data and the difference data, the image data in the low image quality area approaches the original image data, and as a result,
The image quality in the low image quality area is improved. Since the difference data is stored only in the low image quality area, the data amount of the compressed image data is not excessively increased.

[0011]

FIG. 1 is a block diagram showing an image processing system for compressing image data according to an embodiment of the present invention. This image processing system includes an image input device 1 and an image data compression device 2. Image input device 1
Is a reading scanner that reads image data of a document, for example.

The image data compression device 2 includes a CPU 210
And a bus line 220.
0 is connected to a memory 231, a compression / decompression processing unit 232, a difference processing unit 233, and a frame memory 235. The difference processing unit 233 further includes a statistical processing unit 234.
Are connected, and a D / A converter 236 and a CRT 237 are sequentially connected to the frame memory 235. The bus line 220 further includes an interface 241 connected to the image input device 1, a communication interface 242 for communicating with other external devices, and a magneto-optical device for storing a large amount of image data. The disk 243 and the magnetic disk 244 are connected.

FIG. 2 is a flowchart showing a processing procedure of the embodiment. FIG. 3 is a conceptual diagram showing an image to be processed in the embodiment. As shown in FIG.
This image IP includes image portions of a person, a book, and a clock.

In step S 1 of FIG. 2, the image data of the image IP (hereinafter referred to as “original image data”) is read by the image input device 1, and the magneto-optical signal of the image data compression device 2 is transmitted through the interface 241. It is stored on the disk 243.

In step S2, the compression / decompression processing unit 232
Compresses original image data to create compressed image data.
At this time, the operator selects the compression method (Hadamard transform, DC
An irreversible encoding method such as a T-transform) and a compression parameter (a quantization step width, an encoded code, the number of encoded coefficients to be stored, and the like) are selected using a mouse or a keyboard (not shown). The compression ratio changes depending on the compression parameter. A plurality of sets of compression parameters are stored in the magnetic disk 244 in advance, and one of the sets is transferred from the magnetic disk 244 to the compression / decompression processing unit 232 according to an operator's designation. Instead of directly selecting the compression parameter, the operator may specify a compression rank indicating the level of the compression ratio, and the compression parameter corresponding to the compression rank may be read from the magnetic disk 244.

When a compression method based on orthogonal transformation or vector quantization is employed, image data is compressed for each pixel block (for example, a block of 8 × 8 pixels). In this embodiment, compression is performed using discrete cosine transform (hereinafter, referred to as “DCT transform”), which is one of orthogonal transforms.

In step S3, the compressed image data is expanded (restored) by the compression / expansion processing unit 232 to generate expanded image data. The decompressed image data is written to the frame memory 235.

In step S4, the frame memory 235
The restored image is displayed on the CRT 237 based on the decompressed image data written in the CRT 237. The displayed restored image is an image similar to the image shown in FIG. However, at this time, in order to display the entire image IP on the CRT 237,
A reduced image may be generated by thinning out the expanded image data, and the reduced image may be displayed.

In step S5, the operator observes the image displayed on the CRT 237 and determines whether or not the image quality is satisfactory. If the image quality is insufficient, the processing of step S6 and subsequent steps is executed.

In step S6, the difference processing unit 233 and the statistical processing unit 234 extract a pixel block having an image quality of a predetermined level or less from the pixel blocks in the image IP as follows. The difference processing unit 233 calculates a difference (Do-D) between the original image data Do and the decompressed image data Dr.
r) is calculated. Statistical processing unit 2
Reference numeral 34 has a function of calculating a noise component (image quality index) of the decompressed image data Dr based on the difference (Do-Dr). In this embodiment, an S / N ratio is used as an index representing a noise component. The S / N ratio is defined by the following equation. S / N = 20 · log [Dmax / (MSE) ＾ 0.5] (1) Here, the operator “log” represents a common logarithm, and the operator “＾” represents a power. Dmax is the maximum value that can be taken by the image data. For example, Dmax = 255 for 8-bit image data. MSE is a mean square error, and is defined by the following equation. MSE = {[{Do (i, j) −Dr (i, j)} 2] / (M × N) (2) where M is a pixel in the vertical direction of the image to be processed The number N is the number of pixels in the horizontal direction. In addition, i and j are pixel coordinates in the vertical and horizontal directions, respectively. The operator ΣΣ accumulates the values in parentheses from 1 to M for i, and the values in parentheses from 1 to N for j. Is shown.

If the image data is composed of four image data components respectively corresponding to four color inks of yellow (Y), magenta (M), cyan (C) and black (K), The processing unit 234 calculates the S of each color component.
/ N ratio and the average value A of the S / N ratios of the four colors
Calculate sn (dB).

The statistical processing section 234 determines an image quality rank according to the following conditions. Image quality rank 1: 50 <Asn (dB) Image quality rank 2: 45 <Asn ≦ 50 (dB) Image quality rank 3: 40 <Asn ≦ 45 (dB) Image quality rank 4: 35 <Asn ≦ 40 (dB) Image quality rank 5: 30 <Asn ≦ 35 (dB) Image quality rank 6: Asn ≦ 30 (dB) Note that the relationship between the image quality rank and the average value Asn is registered in the statistical processing unit 234 in advance.

The statistical processing unit 234 further extracts pixel blocks having a predetermined image quality rank (for example, image quality rank 6) or less as image quality deterioration blocks. Then, image data for painting out the image quality deterioration block is created. This image data is sent from the statistical processing unit 234 to the frame memory 235.
Supplied to

In step S7, the extracted image quality degraded blocks are specified on the CRT 237. FIG. 4 shows a CRT
FIG. 237 is a conceptual diagram illustrating an example of an image displayed in 237. The image quality deterioration blocks (shown by oblique lines in the figure) are clearly indicated by colors that are easily visible such as red and inverted colors. In FIG. 4, the boundaries of the pixel blocks are also drawn, but the boundaries need not be displayed. In the example of FIG. 4, the image quality of the clock face portion and the text portion of the book greatly deteriorate, so that the pixel blocks including these portions are clearly indicated as the image quality deterioration blocks.

As described above, if the image quality is quantitatively evaluated based on the S / N ratio and the pixel blocks whose image quality level is equal to or less than a predetermined value are specified, the area where the image quality has deteriorated can be identified by the operator. Has the advantage that it can be easily recognized. Furthermore, there is an advantage that the image quality degradation area can be objectively displayed without depending on the experience and skill of the operator.

In step S8, the operator uses a mouse (not shown) to specify a low image quality area. FIG.
Is an explanatory diagram showing how the operator specifies a low image quality area. Here, a first low image quality area L1 including a clock image is specified by a rectangle defined by end points P1 and P2, and end points P3 and P4 The second low image quality area L2 including the image of the book is specified by the rectangle defined by. The low image quality area is an area in which difference data ΔD between the original image data Do and the decompressed image data Dr should be stored.

In step S9, the difference processing unit 233 calculates difference data ΔD for the pixel block including the designated low image quality area. When the image data includes image data components of four colors of YMCK, difference data is calculated for each component. The difference data △ D is further compressed in the compression / decompression processing unit 232 by lossless encoding such as Huffman encoding or irreversible encoding such as DCT encoding. Hereinafter, the compressed difference data is referred to as “compressed difference data”.

In steps S10 and S11, step S
The image is restored based on the compressed image data and the compressed difference data created by the processes up to 9. That is,
First, in step S10, the compressed difference data is decompressed by the compression / decompression processing unit 232, and the difference data obtained by decompression in step S11 is added to the decompressed image data. Then, returning to step S4, step S4
An image restored based on the image data obtained in 11 is displayed on the CRT 237. Since the difference data △ D is stored for the pixel block including the designated low image quality area, when the image is restored based on the image data obtained by adding the difference data to the decompressed image data, the image quality of the low image quality area Has been improved.

Steps S4 to S11 are repeated until the image quality of the entire image IP reaches a satisfactory level. When the image quality of the entire image IP reaches a satisfactory level, the end of the process is specified by the operator, and the process proceeds from step S5 to step S12. Step S12
Then, the compressed image data Dc and the compressed difference data are stored on the magnetic disk 244 as a set of image data representing the image IP (hereinafter, referred to as “compressed image data with difference”).

FIG. 6 is an explanatory diagram showing the file structure of compressed image data with difference. The compressed image data with difference for the image of FIG. 5 includes a first data file F1 including compressed image data Dc, a second data file including compressed difference data for the first low image quality area L1, and F2,
And a third data file F3 including the compressed difference data for the second low image quality area L2.

Various attribute information is written in the header of each data file. As attribute information, a flag indicating whether the data included in the data file is the compressed image data Dc or the compressed difference data, data indicating the image size, a color system (YMCK, RGB, etc.)
And coordinate data indicating an area to which the difference data is applied. The compressed image data with a difference includes a data management table DMT that stores a head address of each data file together with these data files F1, F2, and F3.

When an image is restored based on compressed image data with a difference, the compressed image data Dc is expanded, the compressed difference data is expanded to obtain difference data, and the difference data is added to the expanded image data. Thus, image data representing the restored image is created. By doing so, the decompressed image data is corrected by the difference data in the low image quality area, and the image quality in the low image quality area is improved.

As described above, in this embodiment, difference data is stored for a pixel block including a low image quality area, and an image is restored based on this difference data and decompressed image data. Even in the case where an image area in which satisfactory image quality cannot be obtained only with data occurs, the image quality of the image area can be improved. Also, since the difference data is created only for the pixel blocks including the low image quality area, the image quality of the entire image can be increased to a level that can satisfy the image quality without increasing the data amount of the entire image data much.

The present invention is not limited to the above-described embodiment, but can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

(1) In the above embodiment, the difference data $ D is stored not only for the image quality deteriorated block but also for the low image quality areas L1 and L2 specified by the operator. The difference data ΔD may be stored for only the image quality deterioration block. However, if the difference data ΔD is saved for the low image quality area specified by the operator as in the above embodiment, a remarkable image quality difference is not generated in the restored image restored using the difference data ΔD. There is an advantage that can be. For example, if the difference data ΔD is stored only for the character portion in the image of the same book, the image quality of the character portion in the restored image becomes higher than the image quality of the other portions of the book, and the character portion in the book and the other image portions There is a possibility that a remarkable image quality difference occurs at the boundary with the portion.
On the other hand, if the operator specifies the low image quality area as in the above embodiment, it is possible to prevent such a problem from occurring.

(2) In the above embodiment, the difference data is stored after being encoded and compressed. However, the difference data may be stored without being compressed. However, if the difference data is compressed and stored, there is an advantage that the data amount of the difference-added compressed image data can be further reduced.

(3) In the above embodiment, the image quality is evaluated by calculating the average value Asn of the S / N ratios for the four color image components of YMCK.
The image quality may be evaluated using a value obtained by averaging the S / N ratios of two image components. Further, the present invention is not limited to image data composed of YMCK image components, but is also applicable to compression of image data composed of BGR components and uniform color space components. Further, the present invention is also applicable to image data including only one color image component. In general, the present invention can be applied to compression of multi-valued image data.

(4) In the above embodiment, the S / N ratio, the average value Asn, or the image quality rank is used as the image quality index. However, any other image quality index can be used.

(5) In the above embodiment, the image data is compressed by encoding the image data by the DCT transform. However, the present invention can be generally applied to the case where the multi-value image data is compressed by the irreversible encoding. For example, the present invention can be applied to a case where compression is performed by orthogonal transform coding such as Fourier transform or Hadamard transform or vector quantization coding.

(6) In the above embodiment, the operator has specified the low image quality area so as to include the image quality degraded block. However, if the operator determines that the image quality has been degraded in a portion other than the image quality degraded block, The area may be designated as a low image quality area.

[0041]

As described above, according to the image data compression method of the present invention, the difference data representing the difference between the original image data and the decompressed image data is stored together with the compressed image data in the low image quality area. When restoring an image,
After decompressing the compressed image data to obtain decompressed image data,
By adding the decompressed image data and the difference data, the image data in the low image quality area can be made closer to the original image data, and as a result, the image quality in the low image quality area can be improved. Since the difference data is stored only in the low image quality area, the data amount of the compressed image data is not excessively increased. That is, the image data compression method of the present invention suppresses image quality degradation of a restored image,
In addition, there is an effect that the compression ratio can be increased.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an image processing system for compressing image data by applying an embodiment of the present invention.

FIG. 2 is a flowchart illustrating a processing procedure according to the embodiment;

FIG. 3 is a conceptual diagram showing an image to be processed in the embodiment.

FIG. 4 is a conceptual diagram showing an example of a displayed image.

FIG. 5 is an explanatory diagram showing a state where an operator specifies a low image quality area.

FIG. 6 is an explanatory view showing a file structure of compressed image data with a difference.

[Explanation of symbols]

 Reference Signs List 1 image input device 2 image data compression device 210 CPU 220 bus line 231 memory 232 compression / decompression processing unit 233 difference processing unit 234 statistical processing unit 235 frame memory 236 D / A converter 237 CRT 241 interface 242 communication interface 243 magneto-optical Disk 244 Magnetic disk Do Original image data Dc Compressed image data Dr Decompressed image data DMT Data management table IP image L1, L2 Low image quality area

Claims (1)

(57) [Claims] 1. A method for compressing multi-valued image data by irreversible encoding, comprising: (a) compressing original image data of a processing target image by irreversible encoding for each pixel block of a predetermined size. (B) generating decompressed image data by decompressing the compressed image data; and (c) comparing the original image data with the decompressed image data. Obtaining an image quality index indicating the image quality of the restored image represented by the decompressed image data for each of the pixel blocks; and (d) comparing the image quality index with a predetermined threshold value for each of the pixel blocks (E) identifying a pixel block in which the image quality index does not reach the threshold value as an image quality deterioration block; (F) specifying an image area including the image quality degraded block as a low image quality area; and (g) specifying the original image data for the low image quality area. Obtaining difference data representing a difference from the decompressed image data, and storing the difference data together with the compressed image data.