JPH1051771A - Image compression method and image compression device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To realize an image transfer with a high compression rate without sending or recording an optimum Huffman code table to each image. SOLUTION: A sub band coding section 102 converts image data stored in a frame memory 101 into data on a frequency space. A sub band code storage section 103 stores the result of the sub band coding section 102. An incidence probability calculation section 104 calculates incidence probability of data stored in the sub band code storage section 103. A Huffman code table storage section 105 stores the data incidence probability in the sub band code storage section 103 and the Huffman code table assigned to the data in cross reference. An optimum Huffman code generating section 106 references data in the Huffman code table storage section 105 and decides a Huffman code so that the mean code length is least.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image compression method and an image compression apparatus used for a video phone or the like.

[0002]

2. Description of the Related Art In a high-efficiency encoding technique for an image for a communication medium or a recording medium, an image is once converted into a frequency space, and "natural images have more data at low frequencies than at high frequencies". 2. Description of the Related Art A compression method using sub-band coding utilizing characteristics is widely applied. Furthermore, Huffman coding technology is used to efficiently transmit or record data after subband coding by variable length coding. As a result, images have been compressed to several tenths.

[0003]

However, in the configuration of such a conventional image compression apparatus, since the system-fixed Huffman code table is used, depending on the input image, the probability distribution of the data as a result of subband encoding may be reduced. In some cases, the probability distribution is significantly different from the probability distribution expected in the Huffman code table fixed in the system. In such a case, efficient variable-length coding cannot be performed.

Regarding this problem, a method has been considered in which an optimum Huffman code table is obtained for each image, and the Huffman code table and data encoded using the Huffman code table are transmitted or recorded. I have. In this method, an image cannot be reproduced unless an optimal Huffman code table for one image is transmitted or recorded as data. For this reason, an overhead of transmitting or recording the optimal Huffman code table one image at a time occurs, and there is a problem that the compression ratio of an image that changes with time cannot be improved.

The present invention has been made in view of such conventional problems, and when transmitting or recording an image by compressing it, instead of transmitting or recording an optimum Huffman code table one by one, a learning process is performed. It is an object of the present invention to realize an image compression apparatus and an image compression method capable of outputting an image with a smaller data amount by specifying a representative Huffman code table.

[0006]

According to a first aspect of the present invention, there is provided an image compression method for compressing a time-varying image using sub-band coding. A) for obtaining a list of sub-band codes for each image, step b for obtaining the appearance probability of each sub-band code in the obtained sub-band code list, and It is determined whether or not there is registered in the learned Huffman code table a code that makes the average code length of the Huffman code equal to or less than a predetermined threshold value with respect to the current subband code obtained in steps a and b. And if it is determined in step c that the Huffman code table whose value is equal to or less than the predetermined threshold is registered in the learned Huffman code table, a step of outputting the symbol of the Huffman code table is performed. Tsu and up d, if the Huffman code table for the threshold value or less in step c is determined not to be recorded in the learned Huffman code table, step a,
(b) newly generating an optimal Huffman code table that minimizes the average code length with respect to the current subband code obtained in (b), and adding the optimal Huffman code table obtained in step (e) to the learned Huffman code table. A step f for registering in the code table, a step g for encoding for transmitting or recording the specific Huffman code table generated in the step e, and a step g for registering the current image in the learned Huffman code table. Performing huffman encoding using an optimal Huffman code table and recording or transmitting compressed image data; h.
It is characterized by having.

According to a second aspect of the present invention, there is provided an image compression method for compressing a time-varying image by using sub-band coding. Step a for determining a list of codes; Step b for determining the probability of occurrence of each subband code in the obtained subband code list; and Steps in the trained Huffman code table obtained in the past image, or In the initially learned Huffman code table in which the Huffman code table obtained in advance for the image is registered, the average code length of the Huffman code for the current subband code obtained in steps a and b is determined. And c) determining whether or not a register that makes the Huffman code table to be equal to or less than the predetermined threshold value is registered in the step H. If it is determined that the Huffman code table is recorded in the learned Huffman code table, a step d for outputting the symbol of the Huffman code table, and the Huffman code table to be set to be equal to or less than a predetermined threshold value in the step c, the learned Huffman code table or the If it is determined that it is not recorded in the initially learned Huffman code table, an optimum Huffman code table that minimizes the average code length with respect to the current subband code obtained in steps a and b is newly added. Generating e; registering the optimal Huffman code table obtained in step e in the learned Huffman code table;
Performing a coding step for transmitting or recording the specific Huffman code table generated in step g, and performing Huffman coding on the current image using the optimal Huffman code table registered in the learned Huffman code table. And recording or transmitting the compressed image data.

According to a third aspect of the present invention, there is provided a frame memory for temporarily storing image data for one screen, and a sub-band encoding unit for converting the image data stored in the frame memory into a frequency space. A sub-band code storage unit that stores data of codes converted by the sub-band encoding unit; an appearance probability calculation unit that calculates an appearance probability of each code stored in the sub-band code storage unit; For each code held in the code storage unit, a Huffman code table storage unit that records the appearance probability of each code and a Huffman code for each image, and an appearance probability of each code calculated by the appearance probability calculation unit , Determine the Huffman code so that the average code length of one screen is minimized, and write the Huffman code table into the Huffman code table storage unit, and record the Huffman code table into the Huffman code table storage unit A Huffman code learning unit that collectively stores the Huffman code tables of the obtained images, and in the Huffman code table stored in the Huffman code learning unit, for a subband code of an image that is currently to be encoded, Search for whether there is something that makes the average code length less than or equal to the predetermined threshold, and if there is, output the table number of the Huffman code table,
A learning determination unit that outputs the fact if it does not exist; and a Huffman encoding unit that performs Huffman encoding on the subband code held in the subband code storage unit while referring to the Huffman code table storage unit. And characterized in that:

Further, the invention according to claim 4 of the present application provides a Huffman code table initial learning unit in which an optimum Huffman code table obtained when a typical image is subjected to subband coding is stored in advance, and an image for one screen is provided. A frame memory for temporarily storing data, a sub-band encoding unit for converting image data stored in the frame memory into a frequency space, and a sub-band code for storing code data converted by the sub-band encoding unit A storage unit, an appearance probability calculation unit that calculates the appearance probability of each code stored in the subband code storage unit,
For each code held in the subband code storage unit, a Huffman code table storage unit that records the appearance probability and Huffman code of each code for each image, and each code calculated by the appearance probability calculation unit Huffman code is determined so that the average code length of one screen is minimized, and an optimal Huffman generation unit that writes the Huffman code table storage unit and each image recorded in the Huffman code table storage unit is referred to. A Huffman code learning unit that collectively stores the Huffman code tables, and a subband code of an image that is currently to be encoded in the Huffman code table stored in the Huffman code learning unit or the Huffman code table initial learning unit. In response to this, a search is performed to determine whether or not there is a code whose average code length is equal to or less than a predetermined threshold. If there is, a table number of the Huffman code table is output. A Huffman code learning unit or a Huffman code table initial learning unit for a subband code held in the subband code storage unit with reference to the Huffman code table storage unit. A Huffman encoding unit for performing encoding.

According to the method of the first aspect or the apparatus of the third aspect, when a Huffman code which is one of variable length coding for image compression is used, an optimal Huffman code for a currently input image is used. Learn the table. At this time, if a Huffman code table having high coding efficiency is found in the Huffman code table learned in the past, the symbol of the Huffman code table is output, so that an optimal Huffman code table can be transmitted or recorded. In this way, the information amount of the compressed image data is reduced as compared with the case where the Huffman code table itself is encoded one by one.

According to the method of the second aspect or the apparatus of the fourth aspect, an optimal Huffman code table is obtained in advance for a typical image. In this way, in addition to the above-described operation, an optimal Huffman code table learning effect can be obtained even when a new image is input when the image compression apparatus starts operating.

[0012]

BEST MODE FOR CARRYING OUT THE INVENTION

(Embodiment 1) An image compression apparatus according to a first embodiment of the present invention will be described with reference to the drawings. FIG.
FIG. 1 is a block diagram illustrating a basic configuration of an image compression device according to a first embodiment. In FIG. 1, a frame memory 101 is a memory for storing image data for one screen. The subband encoding unit 102 is a frame memory 101
Is an encoding unit that converts the image data stored in the image data into a frequency space. The subband code storage unit 103 is a storage unit that stores data obtained as a result of conversion by the subband coding unit 102.

The appearance probability calculation unit 104 is a calculation unit that calculates the appearance probability of each of a plurality of data stored in the subband code storage unit 103. Huffman code table storage unit 105
Is a storage unit that stores data appearing in the subband code storage unit 103, the appearance probability of the data, and the Huffman code table assigned to the data in association with each other. The optimal Huffman generation unit 106 determines the Huffman code so as to minimize the average code length by referring to the appearance probability of the code stored in the Huffman code table storage unit 105, and writes the Huffman code to the Huffman code table storage unit 105. is there.

The learning determining unit 107 determines the average code length of the data to be currently encoded after the subband encoding in the Huffman code table stored in the Huffman code table learning unit 108 described later. This is a determination unit that searches whether there is something below the threshold and outputs a symbol (table number) indicating the Huffman code table if it exists, and if not, outputs that fact. The Huffman code table learning unit 108 is a learning unit that stores a plurality of Huffman code tables stored in the Huffman code table storage unit 105.
M. The Huffman coding unit 109 is a coding unit that performs Huffman coding on the data stored in the subband code storage unit 103 with reference to the Huffman code table learning unit 108.

An image compression processing control section 110 is a circuit for controlling the compression processing of each block constituting the image compression apparatus. The image compression processing control unit 110 performs the following control. First, the sub-band encoder 102 is instructed to convert the image data stored in the frame memory 101 into sub-bands. Second, the subband code storage unit 1
Instruct the appearance probability calculation unit 104 to calculate the appearance probability for each code with respect to the data stored in 03.

Third, an optimum Huffman code generator is generated so as to generate an optimum Huffman code table by referring to the relationship between the codes of the Huffman code table stored in the Huffman code table storage unit 105 and the appearance probabilities of the codes. Instruct 106. Fourth, for image data that is currently being subjected to variable length encoding,
When encoding is performed with the Huffman code table learned by the Huffman code table learning unit 108, the learning determination unit 107 is instructed to determine whether the average code length is equal to or less than a certain threshold.

Fifth, the Huffman coding unit 109 is instructed to perform Huffman coding on the data stored in the subband code storage unit 103 with reference to the Huffman code table in the Huffman code table storage unit 105. I do.

The operation of the image compression apparatus according to the first embodiment configured as described above will be described with reference to the flowchart of FIG. First, in step S1, the image compression processing control unit 110 instructs the subband encoding unit 102 to perform subband encoding. Then, the subband encoding unit 102 performs subband encoding with reference to the contents of the frame memory 101 and writes the result in the subband code storage unit 103.

Next, in step S2, the image compression processing control unit 110 instructs the appearance probability calculation unit 104 to calculate the appearance probability of each code with respect to the subband encoding result.
Then, the occurrence probability calculation unit 104 stores the subband code storage unit 1
With reference to FIG. 03, the appearance probability of each code is calculated and written to the Huffman code table storage unit 105. FIG. 3 shows the contents of the Huffman code table storage unit at this time. In this state, the Huffman code has not been determined.

Next, in step S3, the image compression processing control unit 110 gives an instruction to the learning determination unit 107, and when the currently focused subband encoded data is subjected to Huffman encoding, the previously learned Huffman In the code table, a search is made to see if a Huffman code table that can make the average code length equal to or less than a certain threshold has not been learned. Then, the learning determination unit 107 refers to the Huffman code table learning unit 108, and calculates the average code length when the currently focused sub-band coded data is coded using the already learned Huffman code table. I do.

If the value of the calculated average code length is smaller than a certain threshold value, the flow advances to step S8 to output a symbol indicating the Huffman code table of interest. If the value of the average code length calculated here is larger than a certain threshold value, the average code length is calculated for the subband encoded data using the next Huffman code table learned in the past. .

Here, in step S3, if there is no Huffman code table that makes the average code table equal to or smaller than the threshold value, the fact is output, and the process proceeds to step S4.

Here, a description will be given of an operation in the case where a code table that allows the average code length to be equal to or less than the threshold value 10, for example, has not been learned in step S3. In step S4, the image compression processing control unit 110 instructs the optimal Huffman generation unit 106 to generate a Huffman code table. Then, the optimal Huffman generation unit 106 refers to the appearance probability recorded in the Huffman code table storage unit 105, assigns a Huffman code with the shortest average code length to each code, and writes the result to the Huffman code table storage unit 105. . FIG. 4 shows the contents of the Huffman code table storage unit 105 at this time.

In step S5, the image compression processing control section 110
Refers to the Huffman code table learning unit 108 again and outputs the correspondence between codes and Huffman codes. At this time, this code table is written in the Huffman code table storage unit 105. Note that since the storage capacity of the Huffman code table learning unit 108 is finite, the frequency and the like referred to as learning data are stored, the less frequent one is deleted, and the Huffman code table to be newly learned is stored. Needless to say, a sufficient capacity may be secured.

Next, at step S6, the image compression processing control unit 1
Reference numeral 10 encodes a Huffman code table in which the codes of the newly learned Huffman code table are associated with Huffman codes. As described above, when a new learning occurs, the correspondence between the codes of the Huffman code table and the Huffman codes at that time is passed to the reproducing side, and the reproducing side reproduces the original image based on this information. it can.

Next, in step S7, the image compression processing control section 110 instructs the Huffman coding section 109 to perform variable length coding. Then, the Huffman coding unit 109 performs Huffman coding on the contents of the subband code storage unit 103 based on the Huffman code table stored in the Huffman code table storage unit 105.

As described above, the reproducing side receives the information obtained by associating the code with the Huffman code and the data after the sub-band coding which is coded based on the Huffman code table, and thereby the original image is obtained. Can be played.

Next, the operation when the Huffman code table learning unit 108 finds one that makes the average code table equal to or smaller than the threshold value 10 in step S3 will be described. As shown in FIG. 5, it is assumed that C of the Huffman code table stored in the Huffman code table learning unit 108 is a code table that sets the average code length to a threshold value of 10 or less. In step S8, the image compression processing control unit 110 receives the Huffman code table, for example, the symbol “C” output by the learning determination unit 107, and outputs this as a header of the compressed data of the image.

Next, in step S7, the image compression control unit 110 instructs the Huffman coding unit 109 to perform variable length coding. Then, Huffman coding section 109 stores the contents of subband code storage section 103 in Huffman code table storage section 105.
Performs Huffman coding based on the Huffman code table stored in the Huffman code table.

As described above, information indicating that the Huffman code table “C” was used, and Huffman-encoded data using the Huffman code table were prepared. Thus, if the reproducing side also learns the Huffman code table “C”, it can reproduce the original image by transmitting or recording the information.

(Embodiment 2) Next, an image compression apparatus according to a second embodiment of the present invention will be described with reference to FIGS. FIG. 6 is a block diagram showing a basic configuration of an image compression device according to the second embodiment. 6, a frame memory 201 is a memory for storing image data for one screen. The subband encoding unit 202 is an encoding unit that converts image data stored in the frame memory 201 into a frequency space. The sub-band code storage unit 203 is a storage unit that stores data converted by the sub-band coding unit 202.

The appearance probability calculation unit 204 is a calculation unit for calculating the data stored in the subband code storage unit 203 and the appearance probabilities of the data. The Huffman code table storage unit 205 is a storage unit that stores data appearing in the subband code storage unit 203, the appearance probability of the data, and the Huffman code table assigned to the data in association with each other. The optimal Huffman generation unit 206 refers to the code appearance probability held in the Huffman code table storage unit 205, determines the Huffman code so that the average code length is the shortest, and writes the Huffman code into the Huffman code table storage unit 205. is there.

The learning determination unit 207 includes a Huffman code table stored in a Huffman code learning unit 108 described later.
For the data after subband coding of the image to be currently coded, a search is made to determine whether or not there is any data whose average code length is equal to or smaller than a certain threshold value. If there is, a symbol indicating the Huffman code table (table number ) Is output, and if not, it is output to that effect.

The Huffman code table initial learning unit 208 is a memory that obtains an optimal Huffman code for the result of subband coding of a typical image and stores it in the same format as the Huffman code table storage unit 205. .

The Huffman code table learning unit 209 is a learning unit that stores a plurality of Huffman code tables stored in the Huffman code table storage unit 205. Huffman code table initial learning unit 208
Is composed of a ROM, and the Huffman code table learning unit 209 stores
AM. The Huffman coding unit 210 is a coding unit that performs Huffman coding on the data stored in the subband code storage unit 203 with reference to the Huffman code table storage unit 205.

The image compression processing control section 211 is a circuit for controlling the compression processing of each block constituting the image compression apparatus. The image compression processing control unit 211 performs the following control. First, the sub-band encoder 202 is instructed to convert the image data stored in the frame memory 201 into sub-bands. Second, the subband code storage unit 2
Instruct the appearance probability calculation unit 204 to calculate the appearance probability of each code with respect to the data stored in 03.

Third, by referring to the relationship between the codes of the Huffman code table stored in the Huffman code table storage unit 205 and the appearance probabilities of the codes, an optimum Huffman generation unit is generated so as to generate an optimal Huffman code table. Instruct 206. Fourth, the learning determination unit 207 uses the Huffman code table learned by the Huffman code table initial learning unit 208 or the Huffman code table learning unit 209 to convert each code with respect to the image data currently to be subjected to variable length coding. When encoding, the learning determination unit 2 determines whether the average code length is equal to or less than a certain threshold value.
07.

Fifth, the Huffman encoding unit 210 refers to the Huffman code table learning unit 209 or the Huffman code table initial learning unit 208 to convert the data stored in the subband code storage unit 203 into Huffman encoding data. To perform

The operation of the image compression apparatus according to the second embodiment having the above-mentioned configuration will be described with reference to the flowchart of FIG. First, in step T1, the image compression processing control unit 211 instructs the subband encoding unit 202 to perform subband encoding. Then, the subband encoding unit 202 performs subband encoding with reference to the contents of the frame memory 201 and writes the result to the subband code storage unit 203.

Next, in step T2, the image compression processing control unit 211 instructs the appearance probability calculation unit 204 to calculate the appearance probability of each code with respect to the subband encoding result.
Then, the appearance probability calculation unit 204 sets the subband code storage unit 2
03, the appearance probability of each code is calculated and written to the Huffman code table storage unit 205. FIG. 8 shows the contents of the Huffman code table storage unit 205 at this time. In this state, the Huffman code has not been determined.

Next, in step T3, the image compression processing control section 211 gives an instruction to the learning determination section 207, and when the currently focused subband encoded data is Huffman-coded, the previously learned Huffman A search is performed to determine whether a Huffman code table that can make the average code length equal to or less than a certain threshold has been learned in the code table. Then, the learning determination unit 207 refers to the Huffman code table initial learning unit 208 and the Huffman code table learning unit 209, and encodes the currently focused subband coded data using the learned Huffman code table. The average code length in the case is calculated.

Here, in step T3, if a Huffman code whose average code length can be made smaller than a certain threshold is found, the process proceeds to step T8, and a symbol indicating the code table is output. Further, the contents of the code table are stored in the Huffman code table storage unit 20.
After writing in 5, the process proceeds to step T7. If there is no Huffman code that can make the average code table smaller than a certain threshold, that fact is output, and the process proceeds to step T4.

Here, a description will be given of the operation in the case where a code table that can make the average code length smaller than the threshold value 10, for example, has not been learned in step T3. In step T4, the image compression processing control unit 211 instructs the optimal Huffman generation unit 206 to generate a Huffman code table. Then, the optimal Huffman generation unit 206 refers to the appearance probability recorded in the Huffman code table storage unit 205, assigns a Huffman code with the shortest average code length to each code, and writes the result to the Huffman code table storage unit 205. . FIG. 9 shows the contents of the Huffman code table storage unit 205 at this time.

In step T5, the image compression processing control section 211
Refers to the Huffman code table storage unit 205 again and outputs the correspondence between codes and Huffman codes. At this time, the code table is written in the Huffman code table learning unit 209. Note that since the storage capacity of the Huffman code table learning unit 209 is limited, the frequency and the like referred to as learning data are stored, those with low frequency are deleted, and the Huffman code table to be newly learned is stored. The capacity required for the operation may be secured.

Next, at step T6, the image compression processing control unit 2
11 refers to the Huffman code table storage unit 205 and encodes a Huffman code table in which codes are associated with Huffman codes.
In this way, when a new learning occurs, the correspondence between the codes of the Huffman code table and the Huffman codes at that time should be passed to the reproducing side, and the reproducing side can convert the original image based on this information. Can be played.

Next, at step T7, the image compression processing control section 211 instructs the Huffman coding section 210 to perform variable length coding. Then, the Huffman coding unit 210 performs Huffman coding on the code in the subband code storage unit 203 based on the Huffman code table stored in the Huffman code table storage unit 205 or the Huffman code table initial learning unit 208.

As described above, when a new learning occurs, the correspondence between the codes of the Huffman code table and the Huffman codes at that time is passed to the reproducing side, and the reproducing side reproduces the original image based on this information. Can be played.

Next, in step T3, as shown in FIG. 10, the Huffman code table symbol "Y" stored in the Huffman code table learning unit 209 is a code table that makes the average code length equal to or less than the threshold value 10.

In step T8, the image compression processing control unit 21
1 receives the symbol “Y” output by the learning determination unit 207 and outputs this as the header of the compressed data of the image.

Next, at step T7, the image compression control section 211 instructs the Huffman encoding section 210 to perform variable length encoding. Then, Huffman coding section 210 stores the contents of subband code storage section 203 in Huffman code table storage section 205.
Performs Huffman coding based on the Huffman code table stored in the Huffman code table.

As described above, information indicating that the Huffman code table “Y” was used and Huffman-encoded data were prepared using the Huffman code table. Thus, if the reproducing side also learns the Huffman code table “Y”, the original image can be reproduced by transmitting or recording such information.

[0052]

As described above, according to the image compression method of the first and second aspects of the present invention, a time-varying image is compressed using sub-band coding, and the compressed image data is recorded or transmitted. By transmitting the table number of the Huffman code table used for image compression, there is no need to record or transmit the data of the Huffman code table itself. Therefore, the total amount of the compressed image data is reduced.

In particular, when the image compression apparatus of the present invention is used in a videophone, the content of each image is often, for example, a person image in a background image, and the image does not change much over time. Therefore, the optimal Huffman code table once learned can be effectively used for each successive image. Also, by storing the Huffman code table that has been initially learned on the receiving side, the compressed image data transmitted from the transmitting side can be expanded and reproduced using the information on the table number of the Huffman code table.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a basic configuration of an image compression device according to a first embodiment of the present invention.

FIG. 2 is a flowchart illustrating an image compression operation of the image compression device according to the first embodiment.

FIG. 3 is an explanatory diagram showing the contents (No. 1) of a Huffman code table in the first embodiment.

FIG. 4 is an explanatory diagram showing the contents (No. 2) of a Huffman code table in the first embodiment.

FIG. 5 is an explanatory diagram of a Huffman code table held in a Huffman code learning unit according to the first embodiment.

FIG. 6 is a block diagram illustrating a basic configuration of an image compression device according to a second embodiment of the present invention.

FIG. 7 is a flowchart illustrating an image compression operation of the image compression device according to the second embodiment.

FIG. 8 is an explanatory diagram showing the contents (No. 1) of a Huffman code table in the second embodiment.

FIG. 9 is an explanatory diagram showing the contents (No. 2) of a Huffman code table in the second embodiment.

FIG. 10 is an explanatory diagram of a Huffman code table held in a Huffman code learning unit according to the second embodiment.

[Explanation of symbols]

 101, 201 Frame memory 102, 202 Subband encoding unit 103, 203 Subband code storage unit 104, 204 Appearance probability calculation unit 105, 205 Huffman code table storage unit 106, 206 Optimal Huffman generation unit 107, 207 Learning determination unit 108 , 209 Huffman code table learning unit 109, 210 Huffman coding unit 110, 211 Image compression processing control unit 208 Huffman code table initial learning unit

Claims (4)

[Claims] 1. An image compression method for compressing a time-varying image using sub-band coding, comprising the steps of: fetching a new image and obtaining a list of sub-band codes for each image; Step b for obtaining the appearance probability of each subband code in the obtained subband code list; and in the learned Huffman code table obtained in the past image,
A step c for determining whether or not a code that makes the average code length of the Huffman code equal to or less than a predetermined threshold is registered with respect to the current subband code obtained in the steps a and b.
And if it is determined in step c that the Huffman code table to be set to be equal to or less than the predetermined threshold is registered in the learned Huffman code table, a step d for outputting a symbol of the Huffman code table; If it is determined that the Huffman code table to be equal to or less than the threshold value is not recorded in the learned Huffman code table, the average code length becomes the minimum with respect to the current subband code obtained in steps a and b. A step e of newly generating an optimal Huffman code table, a step f of registering the optimal Huffman code table obtained in step e in the learned Huffman code table, and a step of registering the specific Huffman code table generated in step e. Encoding for transmission or recording, using the optimal Huffman code table registered in the learned Huffman code table for the current image. Performs Huffman coding, a step h of recording or transmitting the compressed image data,
An image compression method comprising: 2. An image compression method for compressing a time-varying image using sub-band coding, comprising the steps of: fetching a new image and obtaining a list of sub-band codes for each image; A step b for obtaining an appearance probability of each subband code in the obtained subband code list; and a Huffman code previously obtained in a learned Huffman code table obtained from a past image or for a typical image. In the initially-learned Huffman code table in which the code table is registered, the one that makes the average code length of the Huffman code equal to or less than a predetermined threshold value with respect to the current subband code obtained in steps a and b is registered. C) determining whether or not the Huffman code table to be equal to or less than a predetermined threshold value in the step c is recorded in the learned Huffman code table or the initially learned Huffman code table. If it is determined that the Huffman code table is output, the Huffman code table that outputs the symbol of the Huffman code table, and the Huffman code table to be set to be equal to or less than the predetermined threshold value in the step c are the learned Huffman code table or the initially learned Huffman code table If it is determined that the code is not recorded, a new optimal Huffman code table for minimizing the average code length with respect to the current subband code obtained in the steps a and b, e. e) registering the optimal Huffman code table obtained in step e in the learned Huffman code table, and step g of encoding the specific Huffman code table generated in step e for transmission or recording. The image is subjected to Huffman coding using the optimal Huffman code table registered in the trained Huffman code table, and the compressed image data is recorded or transmitted. And step h to be,
An image compression method comprising: 3. A frame memory for temporarily storing image data for one screen, a sub-band encoding unit for converting the image data stored in the frame memory into a frequency space, and the sub-band encoding unit Sub-band code storage unit that stores the data of the generated code, an appearance probability calculation unit that calculates the appearance probability of each code stored in the sub-band code storage unit, and each code that is held in the sub-band code storage unit The Huffman code table storage unit that records the appearance probability of each code and the Huffman code for each image, and the appearance probability of each code calculated by the appearance probability calculation unit is referred to, and the average code of one screen is referred to. Determining a Huffman code such that the length is minimized, and writing an optimal Huffman code to the Huffman code table storage unit; and a Huffman code table for each image recorded in the Huffman code table storage unit. And a Huffman code learning unit that stores the Huffman code learning unit in the Huffman code learning unit. Search for whether or not there is, a learning determination unit that outputs the table number of the Huffman code table if it exists, and if there is not, a learning determination unit that outputs the fact, and is held in the subband code storage unit An image compression apparatus comprising: a Huffman encoding unit that performs Huffman encoding on a subband code while referring to the Huffman code table storage unit. 4. A Huffman code table initial learning unit which stores in advance an optimal Huffman code table obtained when a typical image is subjected to subband coding; a frame memory for temporarily storing image data for one screen; A sub-band encoding unit that converts the image data held in the frame memory into a frequency space; a sub-band code storage unit that stores data of a code converted by the sub-band encoding unit; An appearance probability calculation unit that calculates an appearance probability of each code stored in the unit, and records an appearance probability of each code and a Huffman code for each image for each code held in the subband code storage unit. A Huffman code table storage unit to determine the Huffman code so that the average code length of one screen is minimized with reference to the appearance probability of each code calculated by the appearance probability calculation unit; An optimal Huffman generation unit that writes to the Huffman code table storage unit; a Huffman code learning unit that collectively stores the Huffman code table of each image recorded in the Huffman code table storage unit; and the Huffman code learning unit or the Huffman code table In the Huffman code table stored in the initial learning unit, for the subband code of the image that is currently being coded, search whether there is one that makes the average code length less than or equal to a predetermined threshold, A learning determination unit that outputs a table number of the Huffman code table if present; and a learning determination unit that outputs the fact if it does not exist, and the Huffman code table storage unit for the subband code held in the subband code storage unit. A Huffman encoding unit that performs Huffman encoding using the Huffman code learning unit or the Huffman code table initial learning unit with reference to
An image compression apparatus comprising: