JP2821496B2 - Method of compressing gradation image data - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to a method of compressing gradation image data for compressing gradation image data such as medical images such as X-ray photographs and CT images. BACKGROUND OF THE INVENTION With the advancement of digital technology, digitized gradation images are frequently stored, transmitted, and subjected to various digital image processings. However, a tone image has a larger amount of information than a binary image, and thus has a problem of a large amount of data when the tone image is digitized. In particular, in the case of medical images, the number of pixels and the number of bits required for each pixel when digitizing are enormous, for example, 4 million pixels and 8 to 10 bits in a chest radiograph, which is an efficient method for storing and transferring data. Is bad. Therefore, today, a data compression technique for compressing enormous data of a gradation image including a medical image to make it compact has been spotlighted. Data compression technologies can be broadly classified into lossless compression and irreversible compression.However, lossless compression can only achieve a low compression ratio of about 1/2 to 1/3, so a high compression rate of 1/5 or more can be obtained. Irreversible compression schemes, in particular, transform coding schemes, are attracting attention. Transformable code is an irreversible compression method in which the entire image is divided into small blocks, orthogonal transformation is performed in block units, and the obtained transform coefficients are quantized and encoded. This is the most suitable compression method for compression. In transform coding, the distribution of the AC component of the transform coefficient is
It is known that it is approximated to a Gaussian distribution having a peak at zero, and the quantization of the transform coefficient having such a distribution is performed by a Mid-Riser type quantization including zero in a quantization determination level, and a quantization output level. It has been reported that when classified into Mid-trace type quantization that includes zero, the Mid-trace type quantization has less random noise in the block and is more preferable. However, when a Mid-trace type quantizer is used, there is a drawback that when the compression ratio is increased, a component-specific pattern image appears, which is unnatural when performing image processing such as enlargement, gradation, and frequency processing. There is a problem that the image appears and the fidelity of the restored image is reduced. By the way, the image quality of the restored image when performing the Mid-trace type quantization has a strong correlation with the maximum run length (maximum zero run length) of the transform coefficient AC component quantized to zero in the quantization stage at the time of compression. You can see that. That is, since the image of each block of the restored image is a weighted sum of the component-specific pattern of the transform coefficient AC component quantized to a value other than zero at the time of quantization, the component-specific pattern is used for a block having a long maximum zero run length. The image appears in the restored image. Therefore, in order to suppress the appearance of a component-specific pattern image, it is only necessary to narrow the quantization width of the quantization determination level at which the quantization output level becomes zero to shorten the maximum zero run length of each block. , The compression rate decreases because the average code length increases. Therefore, by examining the maximum zero run length for each block, it is possible to detect a block in which a component-specific pattern image is likely to appear, and obtain a restored image in which the appearance of the pattern image is suppressed by narrowing the quantization width of only the detected block. I realized I could do it. (Object and Configuration of the Invention) The present invention has been made in view of the above points, and
When compressing the data of a gradation image including a medical image using a transform coding method that performs trace-type quantization, the generation of a component-specific pattern image is prevented, and a high-compression rate and high-quality restored image is generated. In order to achieve this object, in order to achieve this object, in a method of compressing gradation image data for quantizing and encoding a transformation coefficient obtained by performing orthogonal transformation on digitized gradation image data, the conversion coefficient The quantization width is determined based on the maximum run length of the conversion coefficient quantized to zero among the above, and the conversion coefficient is quantized with the determined quantization width. (Example) Hereinafter, the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing an embodiment of a gradation image data compression method according to the present invention. In the figure, a frame memory 1 stores gradation image data to be compressed (the number of bits per pixel is 8 bits in this example). Reading is performed in block units (in this example, the block size is 16 pixels in each of the line direction and the column direction). The read block data is converted into a two-dimensional discrete cosine transform (2D-DC
T) The cosine transform is performed by the device 3 to obtain 256 transform coefficients for one block. Next, of the 256 transform coefficients thus obtained, 255 transform coefficient AC components excluding one DC component are uniformly quantized by the quantizer 4 with a basic quantization width w _o , and each transform is performed. A pair of a coefficient number and a polarity number, which are fixed-length codes, is obtained for each coefficient. The pair of the coefficient number and the polarity number is temporarily stored in the block buffer memory 6, and the coefficient number is sent to the classification device 5. The classifying device 5 performs a classifying process based on the coefficient number of one block sent from the quantizing device 4 and the compression ratio parameter input from the terminal 52, and outputs the class number to the encoding device 7. . When the encoding device 7 reads the class number sent from the classification device 5,
A pair of a coefficient number and a polarity number for one block is read from the block buffer memory 6, the fixed-length code (number) of the conversion coefficient AC component is converted into a variable-length code, and output to the terminal 8. The code data is transmitted from the terminal 8 or stored in the memory. FIG. 2 shows an example of the quantization device 4. First, 255 transform coefficient AC components excluding the DC component among the transform coefficients for one block are input from the terminal 41. The absolute values of the 255 conversion coefficients are determined by the absolute value circuit 42, and at the same time, the polarity determination circuit 43 determines whether the conversion coefficients are positive or negative. The polarity determination circuit 43 outputs the determination result to the terminal 47 as a polarity number. Here, the polarity number is represented by a 1-bit code, and is “1” when the conversion coefficient is negative and “0” when the conversion coefficient is positive. On the other hand, the absolute value of the transform coefficient output from the absolute value circuit 42 is divided by the basic quantization width w _o by the division circuit 44. The division result is truncated to the decimal point by a truncation circuit 45 (this result is referred to as a coefficient number) and output to terminals 46 and 47. The terminal 46 is connected to the classification device 5, and the terminal 47 is connected to the block buffer memory 6. The polarity number and coefficient number obtained for one transform coefficient input from the terminal 41 form a pair of two, and are temporarily stored in the block buffer memory 6 from the terminal 47. On the other hand, the DC component of each block has a sufficiently small quantization width w.
It is uniformly quantized by _dc , or temporarily stored in the block buffer memory 6 in the same manner as the other 255 conversion coefficient AC components without performing quantization. FIG. 3 shows the state of quantization of the AC component of the transform coefficient excluding the DC component. The horizontal axis is the value of the conversion coefficient, and the vertical axis is the frequency of occurrence of the conversion coefficient. The number sequence shown in FIG. 3 (a) is the sequence of coefficient numbers (k) output from the truncation circuit 45.
The number sequence shown by (b) is the polarity number (j) sequence output from the polarity determination circuit 43. Next, FIG. 4 shows an example of the classification device 5 when the number of classes is four. The terminal 51 is connected to the terminal 46 in FIG. 2, from which the coefficient number output from the quantization device 4 is input. When the coefficient number is represented by k (k = 0, 1, 2, 3, 4,...), The coefficient number k input from the terminal 51 is converted into a 4-bit primary counter control code C _i ( i = 0,1,
Is converted to 2,3). FIG. 5 (a) shows an example of the counter control LUT 53. On the other hand, a compression ratio parameter P input by the user from a terminal (not shown) is input from the terminal 52. In the case of this example, two types of compression ratios are prepared (P = 0, 1), and the larger the P, the higher the compression ratio. Compression rate parameter P input from the terminal 52, the compression ratio control LUT 54, is converted into 4-bit compression rate control code e _p. FIG. 5 (b) shows an example of the compression control LUT 54. Next OR circuit 55 takes in the compression ratio control code e _p a primary counter control code c _i, obtaining the second-order counter control code d _i of 4 bits is a logical sum of both. d _i ← c _i Ue _p Next, the counter control circuit 56 executes the second counter control code.
d _i is fetched, and four counters from counter 0 to counter 3 in the counter circuit 57 are controlled by the on / off state of each bit of d _i . Each bit of the second-order counter control code d _i is the counter from the lower bit are sequentially 0, the counter 1, counter 2 are correspondence to the counter 3, when the bit on (= 1) corresponding counter control circuit 56 Counter is incremented by +1 and the bit is turned off (=
In the case of 0), the value of a counter buffer (not shown) provided in the counter is compared with the count value at that time without counting up the corresponding counter, and when the count value is larger than the counter buffer value. Only for, replace the counter buffer value with the count value. Therefore, when the counting operation for one block is completed, the maximum zero run length in that block is stored in the counter buffer. In FIG. 5 (c) shows the correspondence between the bits and the counters d _i. Incidentally, c _i, is a similar relationship with each counter holds for e _p. FIG. 6 is a diagram showing the relationship between the compression ratio parameter P or the compression ratio control code ep and the operation range of each counter. For each compression rate parameter P (each e _p), each counter operates only relationship number k of the range indicated by arrows in FIG. 6. However, in this example, the counter 3 operates for all coefficient numbers k regardless of the value of P.
You can know by. Therefore, if another counter similar to the counter 3 is possessed, the counter 3 may be omitted. Next, the comparison processing procedure of the comparison circuit 58 is shown in the flowchart of FIG. The comparison circuit 58 always checks the count value of the counter 3 (F-1). When the count value is less than 255, the comparison circuit 58 is in a standby state. When the count value of the counter 3 is 255, the comparison circuit 58 reads the run length threshold S _p which is output from the run length threshold LUT 59. FIG. 5D shows an example of the run length threshold LUT59. The run length threshold S _p, is a threshold for the maximum zero run length of each block is stored in each counter buffer. The comparison circuit 58 sets the run length threshold value _Sp.
When read, and compares the counter buffer value of the S _p and counter 2 (F-2). As a result, (1) If the run length threshold _Sp is equal to or larger than the counter buffer value of the counter 2, the class number m is set to 3 (F−
3), S _p is smaller than the counter buffer value of the counter 2 is compared with the counter buffer value of S _p and counter 1 (F-4). (2) in comparison to the counter buffer value of the run length threshold S _p and counter 1, if S _p is the counter 1 counter buffer value or sets the class number m to 2 (F-
5), S _p is smaller than the counter buffer value of the counter 1 compares the counter buffer value of S _p and the counter 0 (F-6). (3) In comparison with the counter buffer value of the run length threshold S _p and the counter 0, if S _p is counter buffer values or sets the class number m to 1 (F-7), S _p counter 0 If it is smaller than the counter buffer value, the class number m is set to 0 (F-8). (4) When the class number m is set, the class number m is output from the terminal 510 (F-9), the classification of one block is completed, and the counts of the counters 0 to 3 are counted. The value and each counter buffer value are cleared to zero (F-10). The class number m output from the comparison circuit 58 is a parameter indicating the range of the transform coefficient to be run-length encoded at the time of encoding. That is, the class number is relative to 255 of the AC component of the block is m, the transform coefficient whose absolute value is present within the following ranges 0 or A _m of transform coefficients means that the run-length encoding ( (See FIG. 6). FIG. 8 is an example of the encoding device 7. When the classifying device 5 completes the classifying operation for one block, the encoding device 7 reads the class number m from the terminal 79 (the terminal 79 is connected to the terminal 510 in FIG. 4) and stores the class number m in the quantization LUT 73. One of the tables used for quantization is selected from the four stored quantization tables, and at the same time, a data read command from the block buffer memory 6 is sent to the data read circuit 72. The data reading circuit 72 receives the DC component data from the terminal 71 connected to the block buffer memory 6 and the 255 sets of coefficient numbers k and polarity numbers j.
(J = 0 or 1) is read. If the read data is a DC component, the data is output from the terminal 78. If the read data is a pair of the coefficient number k and the polarity number j, the quantization in the quantization LUT 73 selected by the class number m is performed. The coefficient number k and the polarity number j are converted into the code number 1 by the table. FIG. 9 shows an example of the quantization table in the quantization LUT 73. This example is an example in which the coefficient number k is uniformly divided so that the final quantization state is the uniform quantization shown in FIG. 10, but the coefficient number k may be unequally divided. It is possible, and non-uniform quantization can be performed with a final quantization width that is an integral multiple of the basic quantization width _Wo . Next, an example of the coding procedure of the AC component is shown in the flowchart of FIG. First, the code number 1 output from the quantization LUT 73 is sent to a zero determination circuit 74 having a code passing counter 74a inside (P-1). When the code passage counter 74a receives the code number 1, the code passage count value y is incremented by one (P-2), and the zero determination circuit 74 performs the zero determination of the code number 1 (P-3). If 1 is zero, after incrementing the zero count value z of the zero counter 75 by +1 (P-4), it is determined whether or not the code passage count value y has reached 255 (P-11). On the other hand, if 1 is not zero, it is determined whether the zero count value z is zero (P−
5) If zero, the code 1 is converted into a variable length code hl by the code number LUT76 (P-6) and hl is output from the terminal 78 (P-7) Is the code passage count y equal to 255? It is determined whether it is (P-11). If the zero count value z is not zero the zero count value z is converted by the code LUT77 the variable length code r _z (P-8), was cleared to zero zero count value z (P-9), terminals r _z It is output from 78 (P-10), and it is determined whether or not the code passage count value y has reached 255 (P-11). In the determination of the code passage count value y, if the count value y is not 255, the process returns to the step (P-1) of reading the code number 1 and repeats the above processing. If the code passage count value y is 255 (P-11), it is determined whether the zero count value z is zero (P-
12) If it is zero, the code passage count value y is cleared to zero (P-13), and the encoding operation of the transform coefficient for one block is completed. If Zerokan'unto value z is not zero and code conversion step (P-8), was subjected to zero clear step of zero count value z (P-9), a variable length code r _z output step to the terminal 78 (P-10) The post code passing count value y is cleared to zero (P-13), and the encoding operation of the transform coefficient for one block is completed. FIG. 12 (a) shows an example of the code LUT76. This example is an example using a common Huffman code hl for each class. In the case of performing uniform quantization as in the present embodiment, there is no significant difference in the compression ratio between when the optimal Huffman code hl is used for each class and when the common Huffman code hl is used for each class. Huffman code common to each class
By using hl, a simpler device can be realized. FIG. 12 (b) shows an example of the code LUT77. This example is an example in which a B1 code common to each class is used as a run length code assigned to the zero count value z. When the gradation image data is compressed by the present method, the frequency distribution of each zero run length becomes an exponential function distribution suitable for the B1 code. Therefore, a high compression ratio can be obtained by using the B1 code. In FIGS. 12 (A) and 12 (B), C and 1 take a value of 0 or 1, and are 1-bit codes satisfying ΔC. FIG. 13 shows the data reading order of the data reading circuit 72 in FIG. Since the conversion coefficient of the gradation image tends to have a smaller amplitude as the frequency component increases, the probability of occurrence of a component quantized to zero also increases as the frequency component increases. Therefore, Fig. 13 (a)
Alternatively, as shown in (b), if encoding is performed from the low frequency side toward the high frequency side, the probability of occurrence of a long zero run increases, and effective run length encoding can be performed. FIG. 14 shows an example of a code configuration. FIG. 14 (a) shows a code example of the result of compressing the entire image of one frame, which is composed of a header part, a code of each subsequent block, and a data end code. FIG. 14 (b) shows an example of the header section configuration, which includes the block size (16 in this example), the number of blocks in the image line direction,
Number of blocks in image column direction and compression ratio parameter P
Is stored. FIG. 14 (c) shows an example of the code configuration of each block.
It is composed of a class number m (in this example, a 2-bit fixed-length code), a DC component code (fixed-length code), and a subsequent AC component code sequence (variable-length code sequence). The AC component code string is a coefficient code string (variable length code strings hl ₁ , hl ₂ ,... Hl _g ) composed of q (1 ≦ q ≦ 255) codes as shown in FIG. ) And run length codes (variable length codes r _z ) are alternately arranged. Hereinafter, examples of various parameters used in this embodiment will be described. Basic quantization width w _o = 0.5 A ₀ = 0.5, A ₁ = 1.0 A ₂ = 1.5, A ₃ = 2.0 S ₀ = 128, S ₂ = 50 Note that the above parameter is the information amount per pixel of the original image is n.
The block size is N × N with bits (n = 8 in this example)
When (N = 16 in this example), the block image is represented by f (x,
y), a value obtained by calculating a two-dimensional discrete cosine transform equation (shown in the following equation) representing a transform coefficient matrix by F (u, v) at a floating point. In the present invention, instead of the two-dimensional discrete cosine transform device 3, another orthogonal transform device, for example, 2
A dimensional and discrete Hadamard transform device, slant transform device, or the like may be used. Also, in the present invention, the block size is not limited to the size of 16 × 16, but is 8 ×.
Sizes such as 8, 32 x 32, 64 x 64 are also applicable,
Further, the number of bits per pixel of the original image is not limited to 8 bits. When counting the coefficient number k in a specific section in the classifying apparatus 5, it is also possible to classify based on the length of the maximum run length in one specific section without providing a large number of specific sections. It is also possible to perform classification using the average zero run length in each block as a parameter instead of the maximum zero run length. Further, the classification can be performed by combining the classification parameter in the present invention with other classification parameters. (Effects of the Invention) As described above, in the present invention, by using the maximum run length of the transform coefficient quantized to zero, the image quality of the restored image, particularly the component-specific Quantization based on the degree of occurrence of pattern images becomes possible.For example, for blocks with a long maximum run length, the quantization width is determined so as to shorten the maximum run length, thereby suppressing the occurrence of pattern images and restoring high image quality. Images can be obtained.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of an embodiment of a gradation image data compression method according to the present invention, FIG. 2 is a block diagram of an example of a quantization device shown in FIG. FIG. 3 is a diagram showing a coefficient number and a polarity number obtained by quantizing the transform coefficient AC component in relation to the frequency of occurrence of the transform coefficient. FIG. 4 is a block diagram of an example of the classification device shown in FIG. Fig. 5 (a) shows the counter control LUT, (b) shows the compression ratio control LUT, (c) shows the correspondence between the secondary counter control code and each counter, and (d) shows the run length threshold LUT. FIGS. 6 (a) and 6 (b) show the operation range of each counter in the counter circuit, FIG. 7 is a flowchart showing the comparison procedure of the comparison circuit, and FIG. 8 is the symbol shown in FIG. FIG. 9 is a block diagram of an example of the quantization LUT shown in FIG.
FIG. 0 is an example of a final quantization state, FIG. 11 is a flowchart showing an AC component encoding procedure by the encoding apparatus shown in FIG. 1, and FIGS. FIGS. 13 (a) and (b) show an example of two code LUTs showing the data reading order in the data reading circuit of FIG. 8, and FIGS. 14 (a), (b), (c) and (d). ), (E)
Is a diagram illustrating an example of the contents of a code configuration. 1 ... frame memory, 2 ... readout device, 3 ... 2
Dimensional discrete cosine transform device, 4... Quantizer, 5... Classifier, 6... Block buffer memory, 7.

   ────────────────────────────────────────────────── ─── Continuation of front page       (56) References JP-A-63-246977 (JP, A)                 IEEE TRANSACTIONS                 ON COMMUNICATIONS                 VOL. COM-23 [7] (1975)               p. 785-786

Claims (1)

(57) [Claims] In a gradation image data compression method for quantizing and encoding a transform coefficient obtained by performing orthogonal transform on digitized tone image data, a maximum run length of a transform coefficient quantized to zero among the transform coefficients. Wherein the quantization coefficient is determined based on the quantization width, and the transform coefficient is quantized using the determined quantization width.