JP2000261809A - Image coder coping with feature of picture - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a moving picture coder that decides a group of picture GOP size and a predicted frame interval in response to the feature of a received picture. SOLUTION: A frame memory 3 stores an input picture in advance, an inter- two-picture change analysis section 32 extracts a change between consecutive pictures, a GOP border position decision section 33 decides a GOP border position on the basis of inter-picture change information A from the inter-two-picture change analysis section 32. Then a simple motion retrieval section 34 applies simple motion retrieval to a picture in one GOP on the basis of GOP border position information B and picture information stored in the frame memory 31 to calculate motion feature prediction information C. A prediction frame interval decision section 35 calculates predicted frame interval information D from the motion characteristic prediction information C. The inter-picture change information A, the GOP border position information B, the motion feature prediction information C and the predicted frame interval information D are given to a coding complexity prediction section, which calculates coding complexity prediction information E in each frame coding mode.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image coding apparatus, and more particularly, to an image coding apparatus for performing coding using motion compensation prediction of a digital video signal.

[0002]

2. Description of the Related Art Among high-efficiency coding schemes for coding a continuously input moving picture signal with a smaller code amount, past coding schemes utilizing the motion and correlation between pictures of a picture signal have been developed. There is motion compensation prediction coding that decodes and reproduces an encoded image and uses motion information in small block units from the image. FIG. 8 shows an example of conventional motion compensation prediction coding.

In FIG. 8, an input image signal 1 of a first screen is shown.
Is input by the prediction mode control unit 12, each switch is connected to the respective side, and the input signal is directly input to the orthogonal transformer 3 in order to obtain high coding efficiency. The orthogonal transform is performed using DCT (Discrete Cosine Transform) or the like, and the orthogonal transform coefficient is quantized by the quantizer 4. The quantized coefficients are converted into a variable length code such as a Huffman code by the first variable length encoder 5 and input to the video multiplexer 15.

On the other hand, the quantized coefficients input to the inverse quantizer 6 are inversely quantized, and the image data is restored by the inverse orthogonal transformer 7. The restored image data is stored in the frame memory 9
Is accumulated in The video multiplexer 15 multiplexes the coded data from the first variable length coder 5 and the quantized information 18 from the quantizer 4 to output a coded video data output 1.
Output as 6.

When the input image signal 1 of the next screen is input, each switch is connected to the side contact by the encoding mode control unit 12, and the input image signal 1 It is input to the compensator 10. In the motion compensator 10, a motion vector is detected from the input image signal 1 and the reference image input from the frame memory 9, and the motion vector is detected by the position shifter 11 and the second variable length encoder 1
4 is input. In the second variable length encoder 14, the motion vector information is converted into a variable length code such as a Huffman code and input to the video multiplexer 15.

The position shifter 11 extracts an image signal specified by a motion vector from the frame memory 9,
It is output to the prediction signal subtractor 2 and the local decoding adder 8 as a motion compensation prediction signal. The motion compensation prediction signal is subtracted from the input image signal 1 by the prediction signal subtractor 2, and the prediction error is encoded. The prediction error signal is orthogonally transformed using a DCT (Discrete Cosine Transform) in the orthogonal transformer 3 in order to obtain a high coding efficiency, and the signal quantized by the quantizer 4 is converted into a first variable-length encoder 5. Is converted into a variable length code such as a Huffman code. Further, in order to use the same prediction signal as that on the decoding side, the quantization coefficient obtained by the quantizer 4 is inversely quantized by the inverse quantizer 6, and the prediction error signal is locally decoded by the inverse orthogonal transformer 7. . Further, the motion compensation prediction signal is added to the prediction error signal restored by the local decoding adder 8,
It is stored in the frame memory 9.

In the coding of a moving image, the coding efficiency can be improved by performing the coding using the motion and the correlation between the images. However, the coding of the image at an arbitrary point in time from the coded moving image can be improved. When decoding and reproducing, the reference image used in the motion compensation prediction must also be decoded and reproduced in advance, so that decoding and reproduction of all images must be performed unless decoding from the beginning of the encoded image is performed. Can not do. In order to solve this problem, by periodically inserting an intra-frame predictive coded frame that can be decoded independently of the past decoded and reproduced image, it is possible to maintain the coding efficiency while maintaining the coding efficiency. Decoding from other sources is possible.

In the coding of moving images, the following three types of image coding methods are used in combination from the viewpoint of high efficiency coding and convenience of decoding and reproduction.

P frame: unidirectional prediction frame. One of the inter prediction frames. The image is encoded by inter-frame motion compensation prediction encoding from an image encoded in the past. This image is decoded and reproduced, and becomes a reference image for the next P frame encoding. If the similarity between the referenced image and the referenced image is high, the coding efficiency is improved.

B frame: One of the inter-frame prediction frames. It is encoded by inter-frame motion compensation prediction from two temporally preceding and succeeding encoded images. The frame is not used as a reference image.

I frame: an intra-coded frame.
One image is independently encoded without using the motion and correlation between images. Therefore, independent frame decoding is possible.

A combination of the above three types of coding schemes,
The minimum unit of an image group that can be independently decoded is GOP (Grou
p Of Picture). The combination of the encoding methods is called a GOP structure. The first frame to be encoded in one GOP is intra-frame encoding (I frame). FIG. 9 shows an example of a GOP. In FIG. 9, one G
The number of frames included in the OP is called a GOP size, and the interval between P frames or the interval between I and P frames is called a predicted frame interval.

Conventionally, the I-frame insertion interval, that is, the GOP size is set to a fixed value irrespective of the characteristics of an input image, and intra-frame coding is forcibly performed at a fixed number of frames. Therefore, even when the correlation with the reference image is high and there is a possibility that the coding efficiency can be improved by using the inter-frame predictive coding, there is a case where the intra-frame coding must be used.

As for the predicted frame interval, the predicted frame interval having the highest encoding efficiency depends on the characteristics of the image. For example, in the case of a moving image, by shortening the prediction frame interval, the prediction efficiency from the reference image is increased, and the encoding efficiency can be improved. Conversely, when there is little change, the coding efficiency can be improved by increasing the prediction frame interval. However, in the conventional method, the prediction frame interval is fixed to about 0.1 second regardless of the characteristics of the image.

[0015]

In the coding of an image according to the conventional method described above, the inter-frame prediction coding is used even when the input image changes and the inter-frame prediction coding is not effective. Or, despite the fact that effective coding can be performed with inter-frame prediction coding,
Forcibly using intra-frame predictive coding prevents improvement in coding efficiency and improvement in image quality of decoded and reproduced images. In addition, it is also unavoidable that a large fluctuation occurs in the image quality immediately after the image feature change. For example, when a large change such as a scene change is present in the input image,
There is a problem that the image quality fluctuates greatly.

An object of the present invention is to solve the above-mentioned problems of the prior art, and to adaptively change a GOP size and a predicted frame interval according to characteristics of an input image and changes in characteristics of the input image. To achieve improved coding efficiency,
It is still another object of the present invention to provide an image encoding device for stabilizing the encoded image quality.

[0017]

In order to achieve the above object, the present invention detects a degree of change between images from continuously input moving image information, and generates an image based on the detected information. The first feature is that a means for determining the image to which the intra-frame coding method is applied based on the degree of the correlation is obtained. According to this feature, the GOP size is different depending on the image feature.

A second feature of the present invention resides in that a means for detecting a motion feature between input images and determining an optimum prediction frame interval from the feature is provided. According to this feature, the optimal prediction frame interval can be determined based on the feature of the motion between the input images.

Further, after the structure of one GOP is determined and before each frame is encoded, the complexity of the encoding in each encoding method is predicted from the feature amount of the image in the GOP, The third feature is that a means for suppressing a change in image quality by reflecting the change in the code amount control is provided.

According to the above-mentioned features, the conventional fixed GO
This makes it possible to eliminate a significant change in image quality due to a change in an input image and a decrease in encoding efficiency, which cannot be avoided in an image encoding method using a P size and a fixed prediction frame interval.

[0021]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below in detail with reference to the drawings. FIG. 1 is a block diagram showing the configuration of one embodiment of the present invention. In the following description, the encoding device shown in FIG. 8 is used as a moving image encoding method, but the present invention is not limited to this. The same reference numerals as those in FIG. 8 indicate the same or equivalent.

This embodiment is characterized in that the characteristics of the image signal are analyzed from the continuously input image signal, the GOP structure is determined according to the information, and coding processing is performed from the information. is there.

In FIG. 1, a continuously input image signal is subjected to characteristic analysis in a GOP structure determination section 20 to determine a GOP structure according to the input image, and to encode an image based on the information. In this case, the GOP structure information signal 21 is output to the encoding mode control unit 12 and the encoding complexity prediction information 22 is output to the encoding rate control unit 17. The operation other than the above is the same as the operation of the encoding apparatus in FIG.

FIG. 2 is a block diagram showing an embodiment of the processing of the GOP structure determining unit 20 in FIG.
It is. The procedure of the process in FIG. 2, which is the first embodiment of the present invention, will be described. First, continuously input image signals are stored in the frame memory 31. It is assumed that the frame memory 31 can store images of the maximum GOP size.

The inter-image change amount analysis unit 32 calculates the amount of change from the video between each image stored in the frame memory 31 and the immediately adjacent image in time, and the result is obtained. The GOP boundary determination unit 33 converts the inter-image change amount information A
Output to Here, the target image and the immediately preceding image are used for calculating the inter-image change amount information A, but other images may be used.

The GOP boundary position determining unit 33 outputs the inter-image change amount information A output from the inter-image change amount analysis unit 32.
Then, the optimum position for determining the GOP boundary in the frame memory 31 is determined, and the information is output as GOP boundary position information B. By this determination of the GOP boundary position, an image in the frame memory 31 that is older than the determined GOP boundary position becomes one GOP.

Further, in the simple motion search unit 34, after the GOP boundary position determination unit 33 determines the insertion of the I frame position, that is, after determining the size of one GOP, the GOP boundary position determination unit
GOP, which is the I frame insertion position information output from
A reference image is determined from one GOP size image determined from the boundary position information B and the video information stored in the frame memory 31, and a simple motion search is performed between the image and another image. Thus, motion feature prediction information C is output.

Next, a predicted frame interval determining section 35 determines a predicted frame interval based on the motion feature prediction information C input from the simple motion search section 34, and outputs predicted frame interval information D.

The inter-image change amount information A, the GOP boundary position information B, the motion feature prediction information C, and the predicted frame interval information D are input to the coding complexity prediction unit 37, and the coding complexity prediction unit 37 , I, P, and B in each frame coding mode, and outputs the information to the coding rate control unit 38 as coding complexity prediction information E.

The coding rate control unit 38 controls the coding rate by reflecting the coding complexity prediction information E input from the coding complexity prediction unit 37 when coding the input image. The GOP boundary position information B and the predicted frame interval information D are also output to the coding mode control unit 36,
The coding mode control unit 36 determines G based on the information.
The OP structure controls switches at the time of encoding.

After the structure of one GOP in the frame memory 31 is determined, the frame memory 31 outputs an image signal to the prediction signal subtraction unit 2 in FIG. 1 in order to encode each image in the GOP. And the output image signal information is
It is deleted from the frame memory 31.

When the encoding of one GOP is completed, the frame memory 31 accumulates the image continuously inputted after the remaining images in the frame memory 31. After storing the image signal of the maximum GOP size, the frame memory 31 performs a process for determining the next GOP structure, and repeats this process.

Next, the operation of each unit of the GOP structure determining unit 20 of FIG. 2 according to the first embodiment of the present invention will be described in detail.
First, the frame memory 31 stores image signals that are continuously input. The number of stored images is equal to or larger than the maximum GOP size determined at the time of encoding. Frame memory 3
In step 1, an image signal is output to the inter-image change amount analysis unit 32 and the simple motion search unit 34. When the structure of one GOP is determined in the stored image group, an image signal is output to the image encoding device, the output image signal is deleted from the frame memory 31, and Then, a newly input image signal is stored.

Next, the inter-image change amount analysis unit 32 extracts two pieces of image information from the frame memory 31 and calculates the inter-image change amount information A. The calculation method includes a method of determining the absolute difference between pixel information at the same position in two images based on a total amount in a frame, and a method of dividing an image into small blocks and calculating a variance value of pixels for each small block. Then, a method is used in which the variance value is determined based on the total amount of the absolute difference between frames in the frame with the representative value of the small block.

In the former method, for example, as shown in FIG. 10 (a), the pixel values of the images i and j are represented by Pi1, P
, Pin; Pj1, Pj2,..., Pjn are determined by equation (1) in FIG. Also, the latter decision method is
For example, as shown in FIG. 3B, the variance of each small block of the images i and j is represented by σi1, σi2,.
If σj2,..., σjm are determined by the equation (2) in FIG.

Although each pixel value in the above-described determination method is processed using only luminance values, processing using color difference values or processing using both luminance and color difference values is also possible. The inter-image change amount information A calculated by the two-image change amount analysis unit 32 is:
GOP boundary determining unit 33 and coding complexity predicting unit 37
Output to

The GOP boundary position determining unit 33 determines a GOP boundary immediately before the frame when the value exceeds a certain threshold, based on the inter-image change amount information A input from the two-image change amount analysis unit 32. Take. Also, the frame memory 3
From the inter-image change amount information A for all the images in 1, it is also possible to determine the method using the immediately preceding image having the maximum value as the GOP boundary, or the logical sum or logical product of the method using the threshold value and the method using the maximum value. is there. The GOP boundary position information B obtained by the GOP boundary position determination unit 33 is output to the simple motion prediction unit 4, the encoding mode control unit 36, and the encoding complexity prediction unit 37.

In the simple motion search section 34, after one GOP size is determined for an image in the frame memory 31 in the GOP boundary position determination section 33, a simple motion search process is performed to predict the motion information of the image in the GOP. I do.
In order to collect the most accurate motion information, as in the motion search processing in the motion compensator 10 in the moving picture coding apparatus shown in FIG. This is a method of dividing into small blocks, performing a motion search on each of the small blocks, and determining from the motion information for each small block obtained in the processing. However, the processing amount required for the motion search is very large. Size 720
× 480 pixels and the search range is ± 16 pixels, 1
Motion search process of adding more than ³¹ times is required in the images.

Considering that such a process is performed by the simple motion search unit 34, when encoding by this method is performed,
The motion search processing with a large processing amount is performed when the GOP structure is determined.
It is necessary to perform the encoding twice in actual encoding. In order to avoid this problem, a method of using the motion information obtained at the time of determining the GOP structure as the motion information in the motion compensator 10 at the time of image encoding so that the number of times of the motion search process is once. However, in this method, since the operation of the simple motion detection unit 34 is performed before the predicted frame interval is determined, the motion information obtained by the search process of the simple motion detection unit 34 is used in image encoding. It is impossible to use the motion compensator 10 as it is.

Therefore, in the present invention, the simple motion search section 34
Then, a simple motion search process with a small processing amount is performed, and a means for predicting motion information of an image from the information is used. The simple motion search processing will be described below.

First, one image in the determined GOP is selected as a reference image, the reference image is divided into small blocks, and a reduced image in which the small blocks are represented by one representative value is created. Here, for the calculation of the representative value, for example, the variance of all pixel values in the small block can be used. As a method of selecting a reference image, a target GO
The oldest image in P is used, but another image can be selected.

Next, a target image is determined and a reduced image of the image is created in order to grasp the motion characteristics of the reference image. Then, a motion search process using the reduced image of the reference image and the target image is performed. In the present invention, this processing is performed on all images other than the reference image in the GOP, but not all of them.
It is also possible to work with several images selectively.

In this method, a representative value that well reflects image feature information is calculated in units of small blocks, a reduced image is created from representative values of all small blocks in one image, and an image is formed using the reduced image. A simple motion search is performed. FIG. 6 shows the creation of a reduced image. Assuming that the size of the input image is M pixels in the horizontal direction and N pixels in the vertical direction, and the size of the small block is 8 pixels in the horizontal and vertical directions, the representative value of each small block is one value for 64 pixels. When the size of the generated reduced image is a multiple of 8 for both N and M, the size is M / 8 pixels in the horizontal direction and N / 8 pixels in the vertical direction. In addition, the size of the small block is not limited to 8 pixels × 8 pixels, 16 pixels × 16 pixels, and processing of all other rectangular blocks is possible.

In this method, the variance of all pixel values in a small block is used to calculate a representative value for each small block.
It is also possible to use the average value, the standard deviation value, or the sum of absolute errors with the average value, or use a combination of each. Here, a luminance value is used as a pixel value, but it is also possible to use a chrominance value or both a luminance value and a chrominance value.

In a general motion search process, a motion search is performed in units of small blocks to calculate a vector indicating a position having the smallest difference amount. Since the reduced image is used, the accuracy of the motion vector information is low. Therefore, as an index of the magnitude of the motion of the entire image, the motion compensation prediction error amount at the position where the motion compensation prediction error is lowest in the motion search using the reduced image information is set as the motion feature value in the image. Also,
For calculating the motion compensation prediction error, a square error amount, an absolute error amount, and an absolute error amount in a square root can be used. Compared to motion search using a general original image pixel information, to create a reduced image obtained by the small block 16 pixels, in the case of the simple motion search becomes a process of adding about 2 ¹³ times, generally 1/100 of the amount of calculation in a simple motion search process
000 or less. The obtained motion feature prediction information C is output to the prediction frame interval determination unit 35.

The motion compensation prediction error amount obtained by a simple motion search between a reference image and other images in one GOP is input to the prediction frame interval determination unit 35 as motion feature prediction information C. You. The prediction frame interval determination unit 35 determines a prediction frame interval from the motion feature prediction information C. In coding an image, if the motion or change between images is large, the prediction frame interval is set small, and if the motion or change between images is small, the prediction frame interval is set large, so that the efficiency is maximized. Encoding can be performed. Therefore, first, 1 GO
In order to grasp the motion features over P, all motion feature prediction information between the reference image and other images in one GOP is obtained, and then the average value is obtained. Then, the average value is used as a representative value, and a predicted frame interval is determined based on the representative value. One feature of the present invention is to have an inversely proportional relationship between the predicted frame interval and the obtained average value. In calculating the representative value in one GOP, the maximum value and the minimum value can be used in addition to the method using the average value.

When the resolution of the input image is high, the amount of movement relative to the pixel is large.
The relationship between the image resolution and the optimal predicted frame interval is inversely proportional. Another feature of the present invention is that when determining a predicted frame interval value, an inverse proportional relationship with image resolution information is reflected. Predicted frame interval information D determined
Is output to the encoding complexity prediction unit 37 and the encoding mode control unit 36. The GOP boundary position information B and the predicted frame interval information D are both encoded mode control units 3
And controls the switches when encoding each image based on the information.

The inter-image change amount information A, GOP boundary position information B, motion feature prediction information C, and prediction frame interval information D are input to the encoding complexity prediction unit 37, and are respectively used for I frame, P frame, and B frame. The encoding complexity prediction information E, which is an index of the generated code amount prediction in the encoding in the encoding mode, is calculated and output to the encoding rate control unit 38.

The encoding rate control unit 38 generates a new GO
When the process shifts to the encoding of P, the encoding complexity prediction information in each encoding mode is updated with the encoding complexity prediction information E input from the encoding complexity prediction unit 37.
Conventionally, encoding complexity prediction information used in past frames having the same encoding mode has been used regardless of switching of input images or fluctuations. Therefore, when a large change such as a scene change is present in the input image, there is a problem that the image quality is largely fluctuated due to the influence of the coding complexity prediction information of the uncorrelated frame. However, in the present invention, since the prediction is based on the image information to be encoded, such a problem can be solved.

Next, a method of calculating the coding complexity prediction information E for each coding mode will be described. To calculate the encoding complexity prediction information E in the I frame, the image encoded as the I frame is divided into small blocks, the variance of the pixel values of each small block is obtained, and the average of the variance in the screen is calculated.
And a fixed value SI which is a scaling parameter. As the pixel value, luminance information, color difference information, and both can be used.

Further, the variance of the pixel value for each small block, and
If the absolute difference calculated between the variance of the pixel values of the adjacent small blocks is equal to or greater than the threshold value, it is determined that the small block area of the input image contains edge information such as contours. When coding the small block area, the coding rate control unit 38 will reflect the coding amount so that a large amount of code can be allocated.

The encoding complexity prediction information E in the P frame is determined by calculating an average value from all the motion feature prediction information C in the target GOP and by multiplying the average value by a fixed value SP which is a scaling parameter. Further, it is also possible to calculate the encoding complexity prediction information in the I frame by scaling it. The coding complexity prediction information E in the B frame is determined by the product of the coding complexity prediction information in the P frame and a fixed value SB that is a scaling parameter.

Next, a second embodiment of the present invention is shown in FIG. This embodiment has a configuration in which the processing of the encoding complexity prediction unit 37 is omitted from the embodiment of FIG.

Next, a third embodiment of the present invention is shown in FIG. This embodiment has a configuration in which the processing for determining the GOP size is omitted from the second embodiment in FIG. In this embodiment, the GOP size is fixed at a length designated in advance, and in each GOP, the optimal prediction frame interval is adaptively changed from the motion feature prediction information C.

Next, a fourth embodiment of the present invention is shown in FIG. This embodiment has a configuration in which the processing for determining the predicted frame interval is omitted from the second embodiment in FIG. In this embodiment, the predicted frame interval is fixed at an interval designated in advance, and only the GOP size is adaptively changed based on the inter-image change amount information A which is a feature of the input image.

[0056]

As is apparent from the above description, according to the present invention, the GOP size is set according to the characteristics and changes of the input image.
It becomes possible to take P size. For this reason, it is possible to avoid a decrease in coding efficiency and a change in image quality that occur in the case of coding with a fixed GOP size.

Also, from the determined GOP size,
Since the motion feature of the image in the OP is detected and the prediction frame interval according to the motion feature is set, it is possible to take the prediction frame interval according to the motion feature of the input image. For this reason, the encoding efficiency can be improved as compared with the conventional case where encoding is performed at fixed prediction frame intervals.

Further, the conventional apparatus reflects the coding complexity prediction information used in the previous GOP even when the previous GOP and the target GOP have no relation to image characteristics due to a scene change or the like. Significant fluctuations in image quality of a coded image, deterioration, and reduction in coding efficiency have occurred. However, in the present invention, after the encoding of one GOP is completed and before the encoding processing of the next GOP, the encoding complexity prediction information is calculated from the characteristics of the image in the target GOP, so that the image characteristic of the unrelated GOP is calculated. Encoding with stable image quality can be performed without being affected.

FIG. 7 shows the results of a simulation experiment on an image having a scene change according to the MPEG2 system. In the simulation, the GOP size is fixed to 15 frames when compression encoding is performed at an encoding rate of 4 Mbit / s.
In contrast to the coding performed by the conventional apparatus in which the distance between predicted frames is fixed to three frames, the present invention has a small PSNR variation and can improve the image quality by 0.65 dB.

[Brief description of the drawings]

FIG. 1 is a block diagram of a motion compensation prediction encoding apparatus including the present invention.

FIG. 2 is a block diagram illustrating a configuration of a GOP structure determination unit according to one embodiment of the present invention.

FIG. 3 is a block diagram showing a second embodiment of the present invention.

FIG. 4 is a block diagram showing a third embodiment of the present invention.

FIG. 5 is a block diagram showing a fourth embodiment of the present invention.

FIG. 6 is an explanatory diagram of creating a reduced image for a simple motion search.

FIG. 7 is a graph showing a simulation experiment result of the present invention.

FIG. 8 is a block diagram of a conventional motion compensation prediction encoding apparatus to which the present invention is applied.

FIG. 9 is a diagram showing a conventional GOP structure.

FIG. 10 is an explanatory diagram of a calculation method of a change amount between two pixels.

[Explanation of symbols]

10: motion compensator, 12, 36 ... coding mode control unit,
17, 38: coding rate control unit, 20: GOP structure determination unit, 21: GOP structure information signal, 22: coding complexity prediction information, 31: frame memory, 32: change amount analysis unit between two pixels, 33 ... GOP boundary position determination unit, 34: simple motion search unit, 35: predicted frame interval determination unit, 37: coding complexity prediction unit.

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Hiromasa Yanagihara 2-1-15 Ohara, Kamifukuoka-shi, Saitama Prefecture Inside Keddy Research Institute Co., Ltd. (72) Masaru Sugano 2-1-15 Ohara, Kamifukuoka-shi, Saitama Corporation F-term in the Caddy Laboratory (reference) 5C059 KK23 MA05 MA21 MC11 ME01 NN01 NN43 PP06 RB02 TA23 TA46 TB03 TC03 TC10 TD05 TD12 UA02 UA34 5J064 AA02 BA01 BA13 BB13 BC01 BC02 BC26 BD03

Claims (10)

[Claims] 1. For continuously input image signals,
An image coding apparatus for performing image coding using motion compensation prediction between images, comprising: an inter-image change calculating an image change amount between an input image signal and a temporally adjacent input image signal. An image encoding apparatus, comprising: an amount calculating unit; and an intra-frame encoding mode determining unit that determines an intra-frame encoding mode that does not use motion compensation prediction based on the amount of change. 2. For an image signal continuously inputted,
In an image coding apparatus that performs image coding using motion compensation prediction between images, a unidirectionally coded (P) frame interval for performing motion compensation prediction coding is determined from a feature amount between input images. An image coding apparatus comprising a P frame interval determining means. 3. For continuously input image signals,
An image coding apparatus for performing image coding using motion compensation prediction between images, comprising: an inter-image change calculating an image change amount between an input image signal and a temporally adjacent input image signal. Amount calculating means, intra-frame coding mode determining means for determining an intra-frame coding mode not using motion-compensated prediction based on the change amount, and performing motion-compensated predictive coding from the feature amount between input images. P-frame interval determining means for determining a one-way coded (P) frame interval for determining a GOP boundary position based on the determination by the intra-frame coding mode determining means, Wherein the P frame interval in the GOP is determined based on the determination by the image encoding apparatus. 4. The image encoding apparatus according to claim 1, wherein said intra-frame encoding mode determining means is configured to determine whether the intra-frame encoding mode is larger than a predetermined threshold value. An image encoding device, wherein 5. The image encoding device according to claim 1, wherein the inter-image change amount is an absolute difference amount between input images, and an input image divided into small blocks. An image coding apparatus, wherein the calculation is performed using at least one of pixel variance values of a block. 6. The image coding apparatus according to claim 2, wherein said P-frame interval determination means divides the input image into small blocks and uses a representative value for each of the small blocks to perform simple motion compensation. An image coding device, wherein the P frame interval is determined by performing prediction. 7. The image encoding device according to claim 6, wherein the representative value uses one of an average within a small block and a variance value within a small block. 8. The image encoding apparatus according to claim 2, wherein said P-frame interval determining means reduces a frame interval when a motion compensation prediction error value is large, An image coding apparatus, which performs control to increase a frame interval when a compensation prediction error value is small. 9. The image encoding apparatus according to claim 2, wherein the target image is divided into small block units, and a variance value of pixel information of the small block is used to divide the target image in the image. An image coding apparatus comprising means for determining an edge region. 10. The image encoding apparatus according to claim 3, further comprising: a coding complexity prediction unit configured to predict a coding complexity in each coding scheme from a feature amount of an image in the GOP, An image encoding apparatus characterized in that the complexity is reflected in code amount control during encoding.