JPH0670174A - Data quantity reducing method for encoded picture data - Google Patents

Abstract

PURPOSE:To easily reduce the data quantity of encoded code data through small processing quantity by entropy-decoding the encoded data, and generating a quantized orthogonal transformation coefficient, and making a part of a non-zero quantized orthogonal transformation coefficient zero. CONSTITUTION:The inputted code data is decoded by an entropy decoding part 10, and is restored into the quantized orthogonal transformation coefficient Sq. This quantized orthogonal transformation coefficient Sq is supplied to a coefficient value changing part 12, and a part of the non-zero coefficient is converted into a zero coefficient. Then, every time one quantized orthogonal transformation coefficient is decoded, a counter installed in a frequency calculating part 14 is counted up by one, and the value (u, v) of corresponding frequency is determined by referring to a table on the basis of the order of the quantized orthogonal transformation coefficient determined by that coefficient value, and if it is larger than spatial frequency Th, this quantized orthogonal transformation coefficient is changed into the zero coefficient. Further, the quantized orthogonal transformation coefficient in which a part of the coefficient was changed into the zero coefficient by the coefficient value changing part 12 is encoded again by an entropy encoding part 16.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a data amount reduction method for coded image data, which reduces the data amount when transmitting or storing coded image data. In recent years, in order to efficiently handle image data having a very large data amount, a coding technique for compressing image data has been widely used. Although there are many methods for encoding image data, there is a special article in the magazine interface December, 1991, "Understanding and Application of Image Data Compression (pp.129-231).
Page) ”, it is obtained by the process of dividing the image data into blocks, the orthogonal transformation process of performing the orthogonal transformation on the divided image, and the orthogonal transformation process because of the high compression efficiency. The JPEG method, which is a combination of a quantization process for performing a quantization process on the orthogonal transform coefficient and an entropy coding process for performing entropy coding on the quantized transform coefficient obtained by the quantization process, is being used internationally. is there.

By the way, the coded image data (hereinafter referred to as "coded data") has a smaller data amount than the original original image data, but the coded data obtained once has a smaller data amount. It may be necessary to convert to coded data. For example, when adding a new image to the image database of code data, there is not enough free space to convert the code data that has already been stored into code data of a smaller data amount, or This is because when the code data is transmitted from the database to a remote place, it would take too long to transmit the code data as it is.

Therefore, there is a demand for development of a technique for converting encoded image data into code data having a smaller data amount and storing or transmitting it, that is, a technique for reducing the data amount of the code data.

[0004]

2. Description of the Related Art FIG. 10 shows a process of encoding image data according to the JPEG system. The image data is divided into blocks in step S1, and the block divided image is subjected to orthogonal transformation in step S2. In step S3, the orthogonal transform coefficient is quantized, and in step S4, the quantized transform coefficient is subjected to entropy coding such as Huffman coding to obtain code data.

The following method is known as a conventional method for reducing the data amount of code data encoded by an encoding method having such an orthogonal transformation process, a quantization process, and an entropy encoding process. FIG. 11 shows the conventional method 1. In step S1, a decompressed image is generated from the coded data, and the decompressed image is re-encoded under a coding condition having a higher compression rate than the previous coding condition.

FIG. 12 shows a conventional method 2. In step S1, entropy decoding is performed on code data to generate quantized orthogonal transform coefficients, and in step S2, dequantization is further performed to obtain orthogonal transform coefficients. The obtained orthogonal transform coefficient is quantized again in step S3 under a quantization condition with which the compression rate is high, and finally entropy coding is performed in step S4 to obtain coded data.

[0007]

However, the conventional method for reducing the data amount of such coded data has the following problems. First, in the conventional method 1 shown in FIG. 11, it is obvious that the amount of processing is large because the image is restored from the coded data and is encoded again. In addition, the conventional method 2 of FIG.
Since the image data is not restored, the processing amount is smaller than that of the conventional method 1. However, since the decoding is performed to restore the orthogonal transform coefficient by the inverse quantization and then obtain it again, the processing amount is still large. There is a drawback that. Therefore, in each of the conventional methods 1 and 2, there is a problem that it takes a long time due to a large processing amount.

An object of the present invention is to reduce the data amount of code data encoded by an encoding method having an orthogonal transformation process, a quantization process, and an entropy encoding process with a small processing amount. It is to provide a method of reducing the amount.

[0009]

FIG. 1, FIG. 2 and FIG. 3 are explanatory views of the principle of the present invention. [First Invention] FIG. 1 is a diagram for explaining the principle of the first invention.

First, according to the present invention, an orthogonal transform process of calculating transform coefficients by subjecting block data obtained by dividing image data into one or a plurality of blocks to orthogonal transform, and a transform coefficient obtained in the orthogonal transform process. An encoding method including a quantization process for calculating a quantized orthogonal transform coefficient by quantizing, and a first entropy encoding process for performing entropy encoding on the quantized orthogonal transform coefficient obtained in the quantization process. A data amount reduction method of coded image data for reducing the data amount of coded data generated by.

In the data amount reducing method according to the first aspect of the present invention regarding the code data obtained by such an encoding method, [step S1] entropy for entropy decoding the code data to restore the quantized orthogonal transform coefficient. Decoding process, [Step S2] Coefficient value changing process in which some non-zero coefficients of the quantized orthogonal transform coefficients restored in the entropy decoding process are set to zero, and [Step S3] Coefficient value changing process is changed. And a second entropy coding process for entropy coding the subsequent quantized orthogonal transform coefficient.

In the first entropy coding process of coding, one or more zero coefficients exist after the last non-zero coefficient of the series of coefficient values of the quantized transform coefficient of one block to be entropy coded. In this case, the step of encoding the identifier indicating the end of the block after the final non-zero coefficient is included, and in the coefficient value changing step of step S2, step S1
The non-zero coefficient near the final coefficient among the quantized orthogonal transform coefficients reconstructed by the entropy decoding process of is preferentially set to zero. [Second Invention] FIGS. 2 and 3 are diagrams for explaining the principle of the second invention.

The code data targeted by the second invention is
An orthogonal transform process of calculating transform coefficients by applying orthogonal transform to block data obtained by dividing image data into one or a plurality of blocks, and a quantized orthogonal process by quantizing transform coefficients obtained in the orthogonal transform process. For the quantization process for calculating the transform coefficient and the quantized orthogonal transform coefficients for a plurality of blocks obtained in the quantization process, one non-zero coefficient value (A) and consecutive zeros in front of this non-zero coefficient. A process of encoding a plurality of K continuous continuous combination data (A ₁ , Z ₁ ) (A ₂ , Z ₂ ) ... (A _K , Z _K ) consisting of a combination of the number of coefficients (Z) And an entropy encoding process including.

The second aspect of the present invention is applied to such code data.
The data amount reduction method is as follows: [Step S1] Entropy decoding of coded data
Entropy recovery to generate combinatorial data
Restoration in encoding process and [steps S2, S3] entropy decoding process
Of some or all of the K combined data
Combination data (A_I , Z_I ) (A_{I + 1} , Z_{I + 1} ) ・ ・ ・ (A_{I + N-1} ，
Z_{I + N-1} ) However, from 1 ≦ I <K, 1 <I + N−1 ≦ K, the total number N of combination data and the continuous zero value coefficient (Z
_I , Z_{I + 1} ・ ・ ・ Z_{I + N- 1} ) The total number M of
The process of calculating the measured value, and [step S4] the final set constituting the continuous combination data
Non-zero coefficient of combined data (A_{I + N-1} ) A new combination day
Non-zero coefficient (A_new ) And combine with the total value M of zero coefficients
A value obtained by subtracting 1 from the value obtained by adding the consecutive number N (M + N-
1) the number of zero coefficients (Z_new )When
The new combination data (A_new , Z_new ) Is generated
New combination data generation process, and [Step S5] New combination data (A_new , Z_new )
Continuous combination data (A_I , Z_I ) (A _{I + 1} , Z_{I + 1} )
... (A_{I + N-1} , Z_{I + N-1} ) Replacement process
And [Step S6] replaced new combination data (A_new ，
Z_new ) Entropy coding
And a process. [Third Invention] FIG. 4 is a diagram for explaining the principle of the third invention.

The code data targeted by the third invention is
An orthogonal transform process of calculating transform coefficients by performing orthogonal transform on data obtained by dividing image data into one or a plurality of blocks, and a series of coefficient values of quantized transform coefficients obtained in the orthogonal transform process. Generated by an encoding method including an entropy encoding process including a process of encoding an identifier indicating a block end after the final non-zero coefficient when one or more zero coefficients exist after the final non-zero coefficient. To be done.

A data amount reducing method of the third invention for such coded data is as follows: [Step S1] Entropy decoding process of entropy decoding the coded data to restore the quantized transform coefficient, [Step S2] And a erasing process of erasing a code from an arbitrary code of code data to a code immediately before an identifier indicating the end of the block based on the quantized transform coefficient code restored in the entropy restoring process.

Here, in the entropy decoding process of step S1, the code delimiter in the code data and the identifier indicating the block end are output from the entropy decoding result, and in the deletion process of step S2, the entropy decoding process is performed. Based on the output code delimiter and the block end identifier, the code from an arbitrary code of the code data to immediately before the identifier indicating the block end is deleted.

The code of the code data which is the object of the third invention
The entropy coding process of the coding method is shown in FIG.
As described above, the quantum of multiple blocks obtained in the quantization process
The value of one non-zero coefficient (A) for the generalized orthogonal transform coefficient
And a set of consecutive zero coefficients (Z) before its non-zero coefficient
A plurality of consecutive N consecutive combination data (A
₁ , Z₁ ) (A₂ , Z₂ ) ・ ・ ・ (A_N , Z_N ) Sign
Of the entropy of step S1.
The deletion range is determined as the decoding result of the pee coding process.
Output the necessary data for Deletion process of step S2
Then, an identifier indicating the end of the block from the code at any position
Delete the code up to immediately before.

[0019]

Next, the operation of the invention will be described. [First Invention] In the first invention of FIG. 1, first, encoded data is entropy-decoded to generate quantized orthogonal transform coefficients (S
1) A part of the non-zero quantized orthogonal transform coefficient is set to zero (S
2). It is known that the values of the orthogonal transform coefficient (quantized orthogonal transform coefficient) are concentrated in the vicinity of zero, and by making a part of the non-zero quantized orthogonal transform coefficients zero, Variability is small. If the data with less variation is entropy-encoded (S3), the data amount is also reduced. That is, the amount of data can be reduced.

[Second Invention] The second invention of FIGS. 2 and 3 reduces the data amount by replacing a plurality of continuous combination data with one combination data. The continuous combination data, in the encoding method of the code data,
For the quantized orthogonal transform coefficients for a plurality of blocks obtained in the quantization process, one non-zero coefficient value (A) and the number of consecutive zero coefficients (Z) before this non-zero coefficient (A) A plurality of consecutive N pieces of continuous combination data (A ₁ , Z ₁ ) (A ₂ , Z ₂ ) ... (A _N , Z _N ) consisting of a combination (A, Z)
Is encoded.

The second invention is divided into a process of collecting a plurality of combination data (S1 to S3) and a process of creating and encoding new combination data (S4, S5). For example,
(10,5), (15,8), (5,2), (6,5)
When the amount of data is reduced by replacing the four combination data with one combination data, all the non-zero coefficients 10, 15, 5 of the first three combination data are set to 0, so that when combining them into one combination. The total number M of zero coefficients of M = M + N−1 = (5 + 8 + 2 + 5) + 4-1 = 23 is calculated.

Finally, the non-zero coefficient 6 of the last combination data
Only new data is left, and new combination data (6, 23) is generated. That is, the non-zero coefficient value 1 of the first three combination data
This is equivalent to setting the three values 0, 15, and 5 to zero. [Third Invention] The third invention of FIG. 3 reduces the data amount by deleting a part of the data immediately before the block end identifier.

In this case, instead of deleting the code data after entropy decoding, it is necessary to entropy decode the code data in step S1 in order to determine the deletion range of the code data and determine the range in which the code data is deleted. Data should be generated. Specifically, the code delimiter and the block end code are known from the entropy-decoded quantized orthogonal transform coefficient, and the codes from an arbitrary code to immediately before the end code are deleted. Further, in particular, in consideration of the position of the code, when deleting the code from the determined position, the code after the predetermined number is reached by counting the sum of the number of consecutive zero coefficients and the number of non-zero coefficients Should be deleted.

Thus, deleting a part of the code data immediately before the block end identifier is equivalent to changing the value of the quantized orthogonal transform coefficient of the data of the code data to be deleted to zero. Particularly, in this case, the process of replacing the data as in the second invention is not necessary. As described above, in the present invention, the data amount can be reduced with a small processing amount without performing the quantization process, the inverse quantization process, and the like.

The data amount reduction method according to the present invention is
The quantized orthogonal transform coefficients are entropy coded after the quantization process of a plurality of blocks is completed.
If an entropy coding method capable of entropy coding each of two quantized orthogonal transform coefficients, the quantization process and the entropy coding process may be repeated for each quantized orthogonal transform coefficient unit. The orthogonal transform coefficients may be collectively processed.

[0026]

[Embodiment of the First Invention] FIG. 5 is a block diagram showing an embodiment of the apparatus to which the data amount reduction method according to the first invention of the present application is applied. In FIG. 5, an apparatus for reducing the data amount of coded data is an entropy decoding unit 10,
The coefficient value changing unit 12, the frequency calculating unit 14, and the entropy coding unit 16 are included.

The input code data is decoded by the entropy decoding unit 10 and quantized orthogonal transform coefficient Sq.
Restored to. The quantized orthogonal transform coefficient Sq is given to the coefficient value changing unit 12 to convert some non-zero coefficients into zero coefficients. The non-zero coefficient in the reconstructed quantized orthogonal transform coefficient Sq may be selected by any method, but in this embodiment, based on the relationship of the spatial frequency of the quantized orthogonal transform coefficient Sq. The range where the non-zero coefficient becomes the zero coefficient is determined.

That is, the frequency calculating section 14 is provided as a selecting means for setting a part of the quantized orthogonal transform coefficient Sq as a zero coefficient, and a coefficient having a predetermined spatial frequency or higher is set as a zero coefficient. That is, assuming that the horizontal frequency is u and the vertical frequency is v in one quantized orthogonal transform coefficient, the spatial frequency in the two-dimensional space is calculated by (u ² + v ² ), and this spatial frequency (u ² + v ² ) Threshold frequency Th that is predetermined
The larger quantized orthogonal transform coefficient is set as the zero coefficient.

The spatial frequency (u
² + v ² ) As a specific example of the calculation, the horizontal frequency u and the vertical frequency v in each block of the entire image divided into a plurality of blocks are examined, and the order of the quantized orthogonal transform coefficients generated in each block is determined. A table storing frequency values (u, v) as indexes is prepared in the frequency calculation unit 14 in advance.

Every time one quantized orthogonal transform coefficient is decoded by the entropy decoding unit 10, the counter provided in the frequency calculation unit 14 is incremented by one and the quantized orthogonal transform determined by the count value of this counter is added. The value of the corresponding frequency (u,
v) is calculated and the spatial frequency (u ² + v ² ) is calculated. If it is larger than the threshold frequency Th, this quantized orthogonal transform coefficient is changed to a zero coefficient.

The quantized orthogonal transform coefficients, some of which have been changed to zero coefficients by the coefficient value changing unit 12, are re-encoded by the entropy encoding unit 16 to generate coded data with a reduced data amount. In this way, if some of the quantized orthogonal transform coefficients restored from the encoded data by entropy decoding are forced to be zero coefficients, the image quality will be slightly lower than before the change, but the image itself can be restored. So there is no problem. [Modification of Embodiment of First Invention] In the embodiment of the first invention shown in FIG. 5, a quantized orthogonal transform corresponding to a spatial frequency (u ² + v ² ) or more of a frequency threshold Th or more in the frequency calculation unit 14 is performed. The coefficient is changed to a zero coefficient to reduce the amount of data. However, in the target code data generation method,
If only the block end identifier is allowed to be coded following the last non-zero coefficient, as another embodiment, after a certain position (after the order) in the quantized orthogonal transform coefficient obtained in the quantization process. All non-zero coefficients may be forcibly changed to zero coefficients.

That is, in the quantized orthogonal transform coefficient obtained in the quantization process, when many zero coefficients are continuous before the final position of the block, the zero coefficient continuous in the last part is Without coding, only the block end identifier will be coded following the last non-zero coefficient. For this reason, in the quantized orthogonal transform coefficient, if the non-zero coefficient near the block end position is forcibly changed to a zero coefficient and many zero coefficients continue before the block end position, the data amount of code data Can be greatly reduced. [Embodiment of the Second Invention] FIG. 6 is a block diagram showing an embodiment of the second invention of the present application.

In FIG. 6, the apparatus for reducing the data amount of encoded data is composed of an entropy decoding unit 10, a change processing unit 18, a reduction process start / end determination unit 20, an entropy encoding unit 16 and a multiplexer 22. First, the entropy decoding unit 10 detects a quantized orthogonal transform coefficient from the coded data obtained by the coding process of FIG. 7.

In the flowchart showing the encoding process of FIG. 7, the quantized orthogonal transform coefficient obtained in the quantization process is a non-zero coefficient A and a continuous zero coefficient before the non-zero coefficient A. It is characterized in that coded data is obtained by entropy coding after converting into combination data (A, Z) with the number Z. In the encoding of FIG. 7, after the quantized orthogonal transform coefficient is obtained in the quantization process, the leading quantized orthogonal transform coefficient is selected in step S1, and the number of consecutive zero coefficients is determined in the next step S2. The counter Z shown is cleared to Z = 0.

Next, in step S3, it is checked whether the value of the quantized orthogonal transform coefficient currently selected is zero, that is, whether it is a zero coefficient. If it is a zero coefficient, the process proceeds to step S4 and the counter Z is incremented by one. Then, in step S5, it is checked whether or not one block ends, and then in step S6, the next quantized orthogonal transform coefficient is selected and the process returns to step S3. By repeating the processes of steps S3 to S6, the number Z of consecutive zero coefficients is counted.

On the other hand, if the value of the quantized orthogonal transform coefficient selected in step S3 is an effective value other than zero, that is, a non-zero coefficient, the process proceeds to step S8 and the value A of the non-zero coefficient currently being processed. And combination data (A, Z) with the number of consecutive zero coefficients indicated by the counter Z obtained in step S4 are created, and the combination data is entropy-encoded in step S9.

Then, in step S10, one block is finished.
After checking the presence / absence, in step S11, the next quantization
Select the conversion coefficient and return to step S2
After clearing Z to 0, the next processing starts, and one block
Repeat until you finish. By the encoding of FIG. 7, an example
For example, N continuous combination data (A₁ , Z₁ ) (A ₂ , Z
₂ ) ・ ・ ・ (A_N , Z_N ) Is created by entropy marks
Will be coded.

When the end of one block is determined in step S5 or step S10, a block end identification is generated in step S7, and entropy coding is performed. Referring again to FIG. 6, in the entropy decoding unit 10, quantized orthogonal transform coefficient combination data (A ₁ , Z ₁ ) to (A _N , as shown in the encoding of FIG. 7) to (A _N ,
Z _N ) (block end identifier EOB) is restored by entropy decoding and output to the change processing unit 18.

The change processing unit 18 starts the change process for reducing the amount of data when receiving a reduction instruction from the reduction process start / end determination unit 20. When the reduction processing is not performed, the restored quantized orthogonal transform coefficient Sq and the block end identifier EOB are directly input to the multiplexer 22.
And output as coded data via the multiplexer 22.

FIG. 8 is a flow chart showing the processing operation in the apparatus configuration of FIG. In FIG. 8, first, when code data for one block is given, step S1
The counter M indicating the total number of zero coefficients for one block per continuous combination data from the number Z of zero coefficients in the combination data (A, Z) reconstructed in step A and the counter N indicating the number of combination data are 0 respectively. Initialize to.

Next, in step S2, the code data is entropy-decoded to generate combination data or a block end identifier. In step S3, it is checked whether or not the block ends, and then the process proceeds to step S4 to check whether or not the deletion process starts. At this time, if there is an instruction to start the deletion process from the deletion process start / end determination unit 20, step S5
After incrementing the counter N indicating the number of combination data by 1, the value Z indicating the number of zero coefficients of the combination data (A, Z) currently processed in step S6 is added to the counter M, Find the total number M of non-zero coefficients up to the present.

Then, in step S7, the coded data is entropy-decoded in the same manner as in step S2 to obtain one combined data. Then, in step S8, it is checked whether or not the block ends, and then in step S9, it is checked whether or not there is a reduction end instruction from the reduction start / end determination unit 20. If there is no instruction to end the reduction, the process returns to step S5, and the process for the combination data obtained in the immediately preceding step S7 is performed. During the loop processing from step S5 to step S9, the new combination data is processed one after another, but the non-zero coefficient value A of the combination data obtained during this processing is not output.

If it is determined in step S8 that the block has ended and the process proceeds to step S15, after the reduction process is started, all the combination data are not output,
The code data of the block end identifier will be output. That is, the combination data immediately before the start of the reduction process becomes the final combination data of this processing block, and all the subsequent non-zero coefficients are changed to zero.

If the reduction process is completed in step S9 before it is determined that the block is completed in step S8, the process proceeds to step S10 and immediately before step S7.
In a non-zero coefficient A of the resulting combined data (A, Z), and non-zero coefficients A _{ne w} of the new combination data. In other words, the non-zero coefficient A of N-1 combination data after the reduction process is started
Has been deleted. As described above, since the non-zero coefficient A of the N-1 combination data is deleted as zero, the value obtained by adding N-1 to the value of the counter M is set as the total number Z _new of zero coefficients of the new combination data, In step S12, the combined data is entropy coded.

Of course, if the instruction to start the reduction processing is not received in step S4, the code data is directly output in step S14. As the method of instructing the change processing unit 18 to start and end the reduction processing by the reduction processing start / end determination unit 20 provided in FIG. 6, (1) start the reduction processing when a predetermined number of combination data are counted. And (2) outputting the predetermined code data and then instructing the start of the reduction process, and the like.

Regarding the end of the reduction processing after starting the reduction processing, up to the final combination data may be combined into one new combination data, or a fixed number of combination data may be combined into one combination data. You may do it. Of course, the reduction start process and the reduction process may be performed a plurality of times for one block, and the reduction process may be repeated. [Embodiment of the Third Invention] FIG. 9 is a block diagram showing an embodiment of the third invention of the present application, and the apparatus of the embodiment of FIG. 9 comprises an entropy decoding unit 10, a counter 24 and a deletion unit 26. It

For the entropy decoding unit 10, FIG.
The coded data obtained by entropy coding of the combination data obtained by the encoding is input, and therefore the entropy decoding unit 10 restores the combination data of the quantized orthogonal transform coefficients and the block end identifier. The deleting unit 26 does not delete a part of the quantized orthogonal transform coefficient restored by the entropy decoding unit 10, but directly inputs the code data and deletes a part thereof. In order to determine the deletion range of the coded data in the deletion unit 26, the entropy decoding unit 1
0 and a counter 24 will be provided.

In this embodiment, the entropy decoding unit 10 uses the restored combination data (A of the quantized orthogonal transform coefficients).
_The values Z ₁ , Z ₂ , ..., Z _N indicating the number of consecutive zero coefficients are output to the counter 24 from ₁ , Z ₁ ) to ( _AN , Z _N ). The counter 24 counts the number of zero coefficients Z _{1 to} Z _N output from the entropy decoding unit 10, and outputs the count value to the deletion unit 26. The deleting unit 26 deletes the code data from when the count value of the counter 24 exceeds a predetermined value to the block end code EOB.

By partially deleting the code data itself in this way, a reduction in the data amount equivalent to forcibly changing the quantized orthogonal transform coefficient from the beginning of one block to a constant position and thereafter can be achieved. Can be realized with a very simple processing configuration. As another embodiment of the third aspect of the invention shown in FIG. 9, the entropy decoding unit 10 uses the quantized orthogonal transform coefficient combination data (A
₁ , Z ₁ ) to (A _N , Z _N ) are detected, and when a code delimiter at a predetermined fixed position is detected, the deletion unit 26 starts the block end identifier EOB from the fixed position.
The code data up to may be deleted.

[0050]

As described above, according to the present invention, the data amount of code data encoded by the encoding method having the orthogonal transformation process, the quantization process and the entropy encoding process can be simplified with a small processing amount. It is possible to appropriately reduce the data amount when the storage capacity of the code data is insufficient or when the transmission of the code data takes too long.

[Brief description of drawings]

FIG. 1 is an explanatory view of the principle of the first invention.

FIG. 2 is an explanatory view of the principle of the second invention.

FIG. 3 is an explanatory view of the principle showing the processing contents of the second invention.

FIG. 4 is an explanatory view of the principle of the third invention.

FIG. 5 is a block diagram of an embodiment of the first invention.

FIG. 6 is a block diagram of an embodiment of the second invention.

FIG. 7 is a flowchart showing an encoding method of encoded data processed in the second invention.

FIG. 8 is a flowchart showing the processing operation of the second embodiment of the invention.

FIG. 9 is a block diagram of an embodiment of the third invention.

FIG. 10 is a flowchart showing a conventional image data encoding method.

FIG. 11 is a flowchart showing a data amount reduction method as conventional method 1.

FIG. 12 is a flowchart showing a data amount reduction method as conventional method 2.

[Explanation of symbols]

 10: Entropy decoding unit 12: Count value changing unit 14: Frequency calculation unit 16: Entropy coding unit 20: Reduction processing start / end determination unit 22: Multiplexer 24: Counter 26: Deletion unit

Claims (7)

[Claims] 1. An orthogonal transform process for calculating transform coefficients by applying orthogonal transform to block data obtained by dividing image data into one or a plurality of blocks, and quantizing the transform coefficients obtained in the orthogonal transform process. And a first entropy coding process for performing entropy coding on the quantized orthogonal transform coefficient obtained in the quantizing process. A data amount reduction method of encoded image data for reducing the data amount of generated code data, comprising: an entropy decoding process of entropy decoding the code data to restore the quantized orthogonal transform coefficient; and the entropy decoding. Of the quantized orthogonal transform coefficients restored in the process of changing the coefficient value to zero, and changing the coefficient value in the process of changing coefficient value. Data amount reduction method of the encoded image data and having a second entropy encoding process of entropy coding the quantized orthogonal transform coefficients after. 2. The data amount reduction method for coded image data according to claim 1, wherein the first entropy coding process includes a series of coefficient values of quantized transform coefficients for one block to be entropy coded. Including one or more zero coefficients after the final non-zero coefficient, encoding an identifier indicating the end of the block after the final non-zero coefficient, wherein the coefficient value changing step includes: A method for reducing the amount of coded image data, wherein a non-zero coefficient close to a final coefficient among the quantized orthogonal transform coefficients restored by the entropy decoding process is preferentially set to zero. 3. Image data in one or a plurality of blocks
By applying orthogonal transformation to the divided block data
An orthogonal transformation process for calculating a transformation coefficient according to the above, and quantizing the transformation coefficient obtained in the orthogonal transformation process.
Therefore, the quantization process for calculating the quantized orthogonal transform coefficient and the quantized orthogonal transforms for the multiple blocks obtained in the quantization process.
Regarding the conversion coefficient, one non-zero coefficient value (A) and the non-zero coefficient
A sequence consisting of a combination of the number (Z) of consecutive zero coefficients before the coefficient.
Continuous K multiple continuous combination data {(A₁ , Z₁ )
(A₂ , Z₂ ) ・ ・ ・ (A_K , Z_K )} Encoding
A first entropy coding process including the following:
Data amount reduction method of encoded image data for reducing data amount
In this case, entropy decoding is applied to the coded data and combined.
Data {(A₁ , Z₁) (A₂ , Z₂ ) ・ ・ ・ (A_K ，
Z_K )} Is generated, and K combination data restored in the entropy decoding process are generated.
Data of some or all of the data
_I , Z_I ) (A_{I + 1} , Z_{I + 1} ) ・ ・ ・ (A_{I + N-1}, Z
_{I + N-1} )} Continuous zero value coefficient (Z_I , Z_{I + 1} ・ ・ ・
・ Z_{I + N-1} ) Total value calculation process for calculating the total number M of
1 ≦ I <K, 1 <I + N−1 ≦ K) and the last combination data of the continuous combination data.
Non-zero coefficient (A_{I + N-1} ) Is the non-zero coefficient of the new combination data
(A_new ), The total number M of zero coefficients and the number of consecutive combinations N
The value (M + N-1) obtained by subtracting 1 from the value obtained by adding
Number of zero coefficients of combined data (Z_new ) As a new combination
Data (A_new , Z_new ) To generate new combination data
The generation process and the new combination data (A_new , Z_new ) Is the continuous union
Set data {(A_I , Z _I ) (A_{I + 1} , Z_{I + 1} ) ...
(A_{I + N-1} , Z_{I + N-1} )} And the new combination data (A_new , Z
_new ) Entropy-encoding the second entropy code
Data amount of encoded image data characterized by having
Reduction method. 4. The method of reducing the amount of encoded image data according to claim 3, wherein the new combination data (A _new , Z
_A method for reducing the amount of encoded image data, characterized in that _new ) is generated and replaced a plurality of times. 5. An orthogonal transform process for calculating transform coefficients by subjecting block data obtained by dividing image data into one or a plurality of blocks, and a quantization transform obtained in the orthogonal transform process. An entropy coding process including a process of coding an identifier indicating a block end after the final non-zero coefficient when one or more zero coefficients exist after the final non-zero coefficient of a series of coefficient values of the coefficient; In the data amount reduction method of encoded image data for reducing the data amount of code data generated by the encoding method having, an entropy decoding process of entropy decoding code data to restore the quantized transform coefficient, and , Based on the quantized transform coefficient code restored in the entropy restoration process, from an arbitrary code of the code data to immediately before an identifier indicating the end of the block, A method of reducing the amount of coded image data, comprising: a deletion process of deleting a code. 6. The method for reducing the amount of coded image data according to claim 5, wherein the entropy decoding step is a code delimiter in the code data as a result of entropy decoding, and an identifier indicating a block end. In the deleting step, based on the code delimiter and the block end identifier output from the deleting entropy decoding step, the code from any code of the code data up to immediately before the identifier indicating the block end is deleted. A method for reducing the amount of encoded image data, comprising: 7. The method of reducing the amount of coded image data according to claim 5, wherein the entropy coding process is performed on the quantized orthogonal transform coefficients for a plurality of blocks obtained in the quantization process. A plurality of N consecutive continuous combination data {(A ₁ , Z ₁ ) (A) consisting of a combination of one non-zero coefficient value (A) and the number of continuous zero coefficients (Z) before the non-zero coefficient. ₂ , Z ₂ ) ...
.. (A _N , Z _N )} is included, and as a decoding result of the entropy decoding process, the number (Z ₁ , Z ₂ , ... Z) of continuous zero value coefficients of the combination data is included.
_N ) is output, and in the deleting step, the sum of the number of zero-valued coefficients and the number of non-zero-valued coefficients output from the entropy decoding step is counted, and from the code when the count value reaches a predetermined value, A data amount reduction method for encoded image data, characterized in that a code up to immediately before an identifier indicating the end of a block is deleted.