JP3038022B2 - Electronic camera device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an electronic camera device and an electronic camera reproducing device.

[0002]

2. Description of the Related Art An image signal picked up by a solid-state image pickup device represented by a CCD or the like is transferred to a memory card, a magnetic disk,
Alternatively, when recording digital data on a storage medium such as a magnetic tape, the amount of data is enormous. It is necessary to perform some kind of compression on the signal data. For example, in a digital electronic still camera, a photographed image is stored as digital data on a data storage medium such as a memory card or a magnetic disk instead of a silver halide film, so that the image is recorded on a single memory card or a magnetic disk device. The number of possible images must be guaranteed.

Similarly, in the case of a digital VTR (video tape recorder) or the like, a predetermined amount of frames must be recorded without being affected by the amount of image data per frame. That is, it is necessary to reliably record the required number of frames, whether a still image or a moving image.

As a method for compressing image data to cope with such a condition, a coding method combining orthogonal transform coding and entropy coding is widely known. As a representative example, an outline of a method studied in international standardization of still image coding will be described below.

In this method, first, image data is divided into blocks of a predetermined size, and two-dimensional DCT (discrete cosine transform) is performed as orthogonal transform for each of the divided blocks.
Next, linear quantization according to each frequency component is performed, and Huffman coding is performed on the quantized value as entropy (information amount per unit report) coding. At this time, the difference value between the DC component and the DC component of the neighboring block is Huffman-coded. The AC component scans from a low frequency component to a high frequency component called a zigzag scan, and performs two-dimensional Huffman coding from the continuous number of invalid (value 0) components and the value of the valid components that follow. .

The above is the basic part of this system. With this basic portion alone, the code amount is not constant for each image because Huffman coding, which is entropy coding, is used.

Therefore, the following method has been proposed as a method of controlling the code amount. First, the processing of the basic portion is performed, and at the same time, the total code amount of the entire screen is obtained. From the total code amount and the target code amount, an optimal quantization width for approaching the target code amount for the DCT coefficient is predicted. Next, processing after the quantization of the basic portion is repeated using this quantization width. Then, from the total code amount generated this time, the total code amount generated last time, and the target code amount, an optimum quantization width for approaching the target code amount again is predicted. If the predicted quantization width matches the previous quantization width and the total code amount generated this time is smaller than the target code amount, the process is terminated and a code is output. Otherwise, the process is repeated using the new quantization width.

The above operation will be described in detail with reference to FIG. 10. First, as shown in FIG. 10 (a), one frame of image data (one frame image presented in the 576 pixels) are divided into blocks of a predetermined size (for example, blocks A, B, C... Composed of 8 × 8 pixels), and as shown in FIG. Two-dimensional DCT (discrete cosine transform) is performed, and the data is sequentially stored on an 8 × 8 matrix. When viewed on a two-dimensional plane, the image data has a spatial frequency which is frequency information based on the distribution of density information.

Therefore, by performing the DCT, the image data is converted into a DC component DC and an AC component AC, and the DC component DC is placed at the origin position (0, 0 position) on the 8 × 8 matrix.
At the 0 and 7 positions, data indicating the maximum frequency value of the AC component AC in the horizontal axis direction, and
Data indicating the frequency value of the maximum AC component AC in the vertical axis direction is stored at the 7, 0 positions, and data indicating the maximum frequency value of the AC component AC in the oblique direction are stored at the 7, 7 positions. In this case, the frequency data in the directions associated with the respective coordinate positions are stored in such a manner that those having higher frequencies than the origin side appear.

Next, the data stored at each coordinate position in the matrix is divided by a quantization width for each frequency component obtained by multiplying a predetermined quantization matrix by a quantization width coefficient α, thereby obtaining each frequency component. (C), and Huffman encoding is performed on the quantized value as entropy encoding. At this time, for the DC component DC, the difference value from the DC component of the neighboring block is represented by a group number (number of additional bits) and additional bits, the group number is Huffman-coded, and the obtained code word and additional bits are combined. As encoded data (d1,
d2, e1, e2).

Coefficients that are also effective for the AC component AC (values are not “0”) are represented by group numbers and additional bits.

For this reason, the AC component AC performs a scan from a low frequency component to a high frequency component called a zigzag scan, and the continuous number of invalid (value is “0”) components (zero run number) followed by Two-dimensional Huffman coding is performed from the group number of the value of the effective component, and the obtained code word and additional bits are combined to obtain coded data.

The Huffman coding is centered on the peak of the frequency of occurrence in the data distribution of each of the DC component DC and AC component AC per frame image. This is performed by encoding data in a form where bits are allocated so as to increase the number of bits to obtain a codeword.

The above is the basic part of this system.

Since only the basic portion uses Huffman coding, which is entropy coding, the code amount is not constant for each image. Therefore, as a method of controlling the code amount, for example, the following processing is performed. I do.

First, the basic portion is processed using the provisional quantization width coefficient α, and at the same time, the total code amount (total number of bits) generated for the entire screen is obtained (g). This total code amount,
From the target code amount and the tentative quantization width coefficient α used, the optimum quantization width coefficient α for approaching the target code amount for the DCT coefficient is calculated by Newton-Raphson-Iteration (Newton Raphson Iteration) (h).

Next, using the quantization width coefficient α (i), the above-mentioned processing after quantization of the basic part is repeated. Then, from the total code amount generated this time, the total code amount generated last time, the target code amount, the quantization width coefficient α used this time, and the quantization width coefficient α used last time, The quantization width coefficient α that is optimal for approaching the amount is predicted. Then, if the predicted quantization width coefficient α matches the previous quantization width coefficient α, and the total code amount generated this time is smaller than the target code amount, the process ends, and the current The encoded data is output and stored in the memory card (f). If not, the quantization width coefficient α is changed, and the process is repeated using the new quantization width α.

[0018]

As described above, for example, in a digital electronic still camera, the number of images that can be recorded on one memory card, magnetic disk device, or one magnetic tape must be guaranteed. Therefore, the image data is compressed and recorded, and it is desired that the image data can be compressed with high efficiency. These are not only items required for digital electronic still cameras but also for other applications.

However, the above-mentioned compression method based on the international standard scheme employs image information compression such as coding for performing orthogonal transform as represented by discrete cosine transform by blocking image data or predictive coding (DPCM). This is a method of performing pre-processing compression, obtaining the result, quantizing the result, and encoding the quantized output by variable-length coding represented by Huffman coding. Although the image data compression method combined with encoding can perform high-efficiency compression, it uses variable-length coding, so the code amount is not known until the coding is actually completed, and the code amount is controlled. There was a problem that it was difficult to do.

On the other hand, there is a proposal to change the data compression ratio in order to increase the number of images that can be recorded on a recording medium having a limited capacity. For example, as shown in JP-A-63-286078, a mode for recording data as it is,
Switching and using the mode of recording by compression,
Japanese Patent Application Laid-Open No. 1-292987 proposes that a plurality of image quality modes can be selected by switching the degree of compression. Generally, when the compression ratio is increased, the image quality is reduced. Therefore, a mode in which the number of recorded images is prioritized (a low image quality mode) and a high image quality mode in which the image quality is emphasized can be selectively switched according to a user's desire or application. That's why.

In these prior arts, a compression circuit having a compression ratio corresponding to a plurality of image quality modes is separately provided, and these are switched and used according to the image quality mode. The size and cost increase. In these prior examples, switching between the non-compression mode and the compression mode, or selecting one of several types of fixed compression ratios, the compression ratio can be set to an arbitrary value, and a fixed capacity can be set. It is not possible to freely set the number of images that can be recorded on the recording medium according to the user's request.

Even if the high image quality mode and the low image quality mode can be selected, the target code amount per image (per frame) naturally changes due to the difference between these modes, and it is necessary to perform compression encoding in accordance with this. However, depending on the content of the image, the spatial frequency distribution varies, and
If the selected compression ratio is fixed, the data capacity after compression will vary depending on the spatial frequency distribution state. In this case, it is always uncertain how many sheets can be recorded on a recording medium of a fixed capacity, and it is inconvenient in terms of usability because it cannot be known unless actually recorded. Also,
Human perceived color signal bandwidth compared to luminance signal bandwidth
The luminance and chrominance signal components of the image.
Control the quantization width by separating
By reducing the number compared to the signal, the image quality of the reproduced image
Can reduce the amount of information without deteriorating
Become. However, in the above prior art, the luminance signal
The quantization width α was controlled without distinguishing the signal from the color signal.
Therefore, there is a problem that the amount of information increases. Also information
If the volume is large, it takes time to record information, especially
Is a problem for electronic cameras that require
Was. It also states that the amount of image information per frame increases.
Question that the number of recordable images that can be recorded on
There was also a title.

Therefore, an object of the present invention is to enable a desired image quality mode to be selected and to allow a fixed number of images to be photographed and recorded in accordance with the selected image quality mode, or to provide a desired number of images. The number of images can be set, and shooting and recording can be performed for the number of images. Also, it is possible to support various compression ratios with common hardware without preparing hardware for each compression ratio. An object of the present invention is to provide an electronic camera device capable of maintaining the best image quality within the range. The object of the present invention is
Information with small capacity while maintaining high image quality of playback images
By compressing the amount, the number of shootable images is large, and
An object of the present invention is to provide an excellent electronic camera device.

[0024]

In order to achieve the above object, the present invention is configured as follows. That is, it has a photographing system for generating a video signal, and A / D converts an image signal obtained by this photographing system into a luminance signal component and a color signal component.
After performing pre-processing by image information compressing means for performing orthogonal transformation or predictive coding, etc., quantizing by quantizing means, the quantized output is variable-length coded by variable-length coding means, and the variable-length coded image An electronic camera device configured to record and store signal data on a recording medium that records signal data in a readable manner, comprising: input means for inputting information corresponding to a desired compression rate; and a quantum device corresponding to various compression rates. A luminance signal corresponding to the compression ratio corresponding information, based on the compression ratio corresponding information input by the input means, having information of the compression width in advance.
A quantization width setting unit that outputs information of a quantization width for each of the component and the color signal component; and a unit that readablely records the information of the quantization width output from the quantization width setting unit on the recording medium. And the quantization means receives the information on the quantization width output from the quantization width setting means and quantizes the preprocessed image signal data with the quantization width. I do.

[0025]

Secondly , the input means for inputting information corresponding to a desired compression ratio and the output of the variable length coding means are obtained, and the total code amount per screen is obtained, and this is used as calculated code amount information. From the output code amount calculating means and the compression ratio correspondence information input by the input means, information on the total code amount to be stored per image is given, and a statistical processing command is first issued, and the coding is performed when the statistical processing is completed. Control means for issuing a processing command, and at the start of execution by the statistical processing command, based on information on the total code amount from the control means, predicts a quantization width corresponding to the frame of the total code amount and performs the prediction. The quantization width information is provided to the quantization means, and at the start of execution according to the encoding processing command, the quantization width information predicted to be swivel based on the input calculated code amount information falls within the frame of the total code amount. Supplement Quantization width prediction means for obtaining the information of the corrected quantization width and providing the information of the corrected quantization width to the quantization means; and storing the information of the quantization width predicted by the quantization width prediction means in the recording medium. Means for readable recording is provided, and the quantization means receives the information of the quantization width and quantizes the preprocessed image data with the quantization width.

Furthermore, the third input means for inputting the information corresponding to the desired compression ratio, receives the output of the variable length coding means, it seeking total code amount in the unit of a picture as calculated code quantity information From the output code amount calculating means and the compression ratio correspondence information input by the input means, information on the total code amount to be stored per image is given, and a statistical processing command is first issued, and the coding is performed when the statistical processing is completed. Control means for issuing a processing command, and at the start of execution according to the statistical processing command, information on the total code amount from the control means is attached, and a prediction of a quantization width corresponding to the frame of the total code amount is performed. The quantized width information is given to the quantizing means, and at the start of the execution according to the encoding process command, the information of the previously predicted quantization width based on the calculated code amount information inputted is set in the frame of the total code amount. Supplement to fit Quantization width prediction means for obtaining the information of the corrected quantization width and providing the information of the corrected quantization width to the quantization means, and the calculated code amount information and the total code to be contained when executed by the statistical processing command. Code amount allocating means for calculating the allocated code amount of each block based on the amount information, and the calculated code amount information for each block, when executed by the coding processing command, is the allocated code amount in the block. , The variable length coding means controls the coding to stop the coding for the block, and the quantization width information predicted by the quantization width prediction means is recorded in the recording medium in a readable manner. The quantization means receives the information of the quantization width and quantizes the preprocessed image data with the quantization width. Ri to abort the encoding configuration and for the block currently being processed for each receiving a command.

[0028]

Further, having an imaging system for generating a video signal in the fourth, the image signal obtained by the imaging system as well as the image data of this image data into blocks with predetermined pixel units, for the respective blocks After performing orthogonal transform in order to generate coefficient data for each frequency component, quantize by a quantizing means, and quantize the quantized output by a variable length coding means, and read out the variable length coded image signal data. In the electronic camera device, the coefficient data for each frequency component for each block is stored in the quantizing means, and a provisional quantization component for each frequency component is used during statistical processing. To perform quantization in order from the low frequency component, and in the encoding process, perform quantization in order from the low frequency component using the optimal quantization width coefficient for each frequency component. And a calculating means for calculating the code amount of the coded output from the variable-length coding means, a control for performing a statistical process first, and then performing a coding process. The quantization means is controlled to quantize the coefficient data for each frequency component using a predetermined temporary quantization width coefficient for each frequency component in order from each frequency component. The coefficient data for each frequency component is controlled in order from the low frequency component to quantize using the optimal quantization width coefficient for each frequency component, and the occurrence of the statistical processing obtained from the calculation means is controlled. A control means for determining an optimum total code amount to be included in the image from the total code amount and setting the optimum target code amount to the optimum target code amount; Code assigning means for determining an assigned code amount for each block from the total code amount generated per image and the code amount for each block obtained from the code amount information of the variable length encoding means during the encoding process. And a truncation means for terminating the encoding so that the encoded output of each block to be output does not exceed the allocated code amount of the block.

[0030]

According to the present invention, there is provided a photographing system for generating a video signal, and an image signal obtained by this photographing system is preprocessed (for example, divided into blocks and subjected to orthogonal transformation such as DCT or DPCM) by image information compression means. And the like, and the resulting signal is supplied to a quantization means for quantization, the quantized output is subjected to variable-length coding by a variable-length coding means, and the variable-length-coded image signal data is recorded in a readable recording medium. In the case of the first configuration, when information corresponding to a desired compression ratio is input from the input unit, the quantization width setting unit uses the input compression ratio corresponding information. And outputs the information of the quantization width for the luminance signal component and the chrominance signal component corresponding to the quantization signal, and supplies the information to the quantization means and the recording means. More Readably recorded was the information of the quantization width to the recording medium. Further, the quantization means receives the information of the quantization width output from the quantization width setting means and quantizes the preprocessed image signal data with the quantization width. According to this configuration, the quantization width setting means previously stores the quantization width information for the luminance signal component and the chrominance signal component corresponding to various compression ratios, and stores the information in the input compression ratio. The information of the optimal quantization width can be given only by reading corresponding to the corresponding information, so that the encoding process can be performed in a very short time and the hardware can be simplified in order to fit in the target code amount. Will be enough. Further, according to the present invention,
Video signal was separated into a luminance signal component and a chrominance signal component.
Later , using the quantization width information corresponding to each of these components,
Encoding process enables high quality playback images
Can be compressed to a small amount of information while maintaining
An electronic camera that has a large number of images that can be taken
An apparatus can be provided. Also, the information of the quantization width is
By recording on a recording medium, this quantization
Easy and quick image playback using width information
Become.

[0031]

In the second case, when information corresponding to a desired compression rate is input by the input means, the control means obtains information on the total code amount to be stored per image from the input compression rate correspondence information. This is given to the quantization width prediction means. The control means first issues a statistical processing command, whereby the quantization width prediction means predicts the quantization width corresponding to the total code amount frame based on the information on the total code amount from the control means. This is given to the quantization means as provisional quantization width information. The quantization means quantizes the image signal data from the image pickup system by using this, and supplies the quantized image signal data to the image signal compression means to perform variable length coding. On the other hand, the code amount calculation means receives the variable length coded output from the image signal compression means, calculates the total code amount for each screen, and outputs this to the quantization width prediction means as calculated code amount information.

When the statistical processing is completed, the control means issues a coding processing instruction, and the quantization width prediction means uses the calculated code amount information inputted and the information of the previously predicted quantization width to calculate the total code amount. Re-estimate the quantization width that fits in the frame,
The information on the new predicted quantization width is obtained, and the information on the corrected quantization width is given to the quantization means. The preprocessing is performed by the quantization means based on the quantization width based on the information on the quantization width. And quantizes the already processed image data. Further, the recording means records the information of the quantization width predicted by the quantization width prediction means on the recording medium in a readable manner.

In summary, in the second case, a desired compression rate can be given, and even if the total code amount per image (target code amount) changes due to the change in the compression ratio, the designated target Perform the encoding process for investigation such as quantizing with the temporary quantization width information determined by the code amount and performing variable length coding, and perform the prediction of the optimal quantization width from the total code amount obtained as a result, This is a two-pass method in which quantization is performed with the predicted optimum quantization width and final encoding is performed. In this method, encoding processing for investigation is performed, so that the final code amount is set to a target value. It is possible to find the optimum quantization width and fill the target code amount with the inner ring. In addition, since the compression rate can be obtained by hardware that shares all compression rates without using hardware for each compression rate, cost reduction and size reduction can be achieved.

In the third case, the image data is divided into blocks, and the divided blocks are pre-processed by performing an orthogonal transformation or the like, and then quantized by a quantization means, and the quantized output is changed. In the case of performing variable-length encoding by the long encoding unit, when information corresponding to a desired compression ratio is input by the input unit, the control unit uses the input compression ratio corresponding information to determine the total code amount to be contained per image from the input compression ratio corresponding information. Information is obtained and given to the quantization width prediction means. The control means first issues a statistical processing command, whereby the quantization width prediction means predicts the quantization width corresponding to the total code amount frame based on the information on the total code amount from the control means. This is given to the quantization means as provisional quantization width information. The quantization means quantizes the image signal data from the image pickup system by using this, and supplies the quantized image signal data to the image signal compression means to perform variable length coding.

On the other hand, the code amount calculating means receives the output of the variable length coding means, calculates the total code amount for each screen, and outputs this as calculated code amount information. Further, the code amount allocating means obtains the allocated code amount of each block based on the calculated code amount information and the information of the total code amount to be contained.

When the statistical processing is completed, the control means issues a coding processing instruction, and the quantization width prediction means performs the following processing on the basis of the input information of the calculated code amount and the information of the previously predicted quantization width.
Optimum value prediction of the quantization width is performed so as to be within the frame of the total code amount, information on the quantization value predicted by the optimum value is given to the quantization means, and the quantization means is provided based on the information on the quantization width. The pre-processed image data is quantized by the determined quantization width.

The quantized output from the quantizing means is:
The output is variable-length coded by the variable-length coding means. Further, the code amount calculating means receives the output of the variable length coding means, calculates the total code amount for each screen, and outputs the calculated total code amount information as calculated code amount information. Referring to the allocation amount for each block, when the calculated code amount information for each block reaches the allocated code amount in the block at the time of execution according to the coding processing command, the code for the block by the variable-length coding unit is assigned to the block. Control to terminate the conversion. The quantization means receives the information of the quantization width, quantizes the preprocessed image data with the quantization width, and the variable-length coding means outputs the variable-length encoded data. , The coding for the block currently being processed is discontinued. The recording means records the information of the quantization width predicted by the quantization width prediction means on the recording medium in a readable manner.

In short, the third case is a two-pass method in which the processing is completed in two passes, and uses a coefficient α capable of giving a quantization width that can obtain a code amount close to the target code amount. When the statistical processing is performed, the optimum quantization width coefficient α can be found quickly and more accurately, and the optimal quantization width coefficient set based on the target code amount is used as a provisional quantization width coefficient. The first pass quantization is performed using a quantization width coefficient close to the width, and from the obtained total code amount, a quantization width coefficient that can be included in the target code amount is known, and this is used in the second pass. The final encoding is performed by using this function.However, the amount of code is adjusted in units of blocks, and if the amount of code in the block exceeds the allocated amount, the encoding in that block is terminated. It will fit neatly. As a result, the image data can be accurately encoded in a short period of time in the entire frame of the target code amount, thereby making it possible to approach the allowable code amount as much as possible, thereby minimizing lost data and improving image quality. It will be able to maintain. In addition, since the compression ratio can be obtained by hardware that shares all compression ratios without using hardware for each compression ratio, cost reduction and miniaturization can be achieved.

According to the present invention, in a coding apparatus for pre-processing image data, quantizing the output, and variable-length encoding the quantized output, the quantization width of the quantization is set according to a target code amount. It is characterized by being variably set to an optimum value.

Thus, the image data can be quantized by the optimal quantization width so as to be within the target code amount and subjected to variable-length coding.
It is a well-known fact that when this output is quantized and is subjected to variable-length encoding, the amount of code generated varies by changing the quantization width in quantization. This is because variable-length coding represented by Huffman coding reduces the amount of code necessary to represent the data to be coded by utilizing the bias in the occurrence probability of the data to be coded. "To change the width" means to change the probability of occurrence of the quantized value. Therefore, by changing the quantization width, the generated code amount naturally changes.
Even if the same encoding is performed with the same quantization width, the generated code amount differs depending on the image data at that time. But,
When the same encoding is performed on one image data while changing the quantization width, a certain relationship is obtained between the quantization width and the generated code amount. Further, when the relationship between the quantization width and the generated code amount is obtained for a large amount of image data, it becomes clear that the relationship having the highest frequency of occurrence can be obtained statistically. In many cases, the following relationship is obtained. That is, SF is a relative ratio with respect to a certain quantization width, and is represented by the number of bits (bit rate) per pixel generated code amount.
g BR = a × log SF + b If a is the same encoding, it is substantially constant regardless of the image, and b depends on the image. The value of b has a certain distribution depending on the image,
Representative b is obtained from this occurrence frequency distribution.

A feature of the present invention resides in that a quantization width according to a target code amount is set using such a relationship between the quantization width and the code amount. Therefore, according to the present invention, even if the target code amount is changed, the optimum quantization width coefficient α that can provide a quantization width that allows the code amount to become the target code amount in a short time can be obtained. Can be sought,
It is possible to quickly compress to the target code amount, and to obtain the best image quality within the range of each target code amount, and
An electronic camera device capable of reducing hardware cost and size can be provided.

[0043]

[0044]

Further, in the fourth case, when photographing is performed, this image (digitized image) is divided into blocks, and then orthogonal transformation is sequentially performed on each block to obtain coefficient data for each frequency component. Then, the coefficient data for each frequency component is quantized using the provisional quantization component for each frequency component in order from the low frequency component, and this is variable-length coded, and then the total code amount generated by this is calculated. And the optimal target code amount is obtained from the code amount for each block, and the target code amount is distributed by the generated code amount for each block to obtain the allocated code amount for each block. Determine the optimal quantization width for each frequency from the code amount,
The image obtained by the shooting is divided into blocks, and then orthogonally transformed for each block in order to obtain coefficient data for each frequency component, and the coefficient data for each frequency component is sequentially determined from the low frequency component. Perform quantization using another optimal quantization width coefficient, perform Huffman encoding on this, and then record the code generated by the Huffman encoding within the range not exceeding the allocated code amount in the block. Exceeding stops the encoding.

In this configuration, generally, an image in which a large amount of code is generated when coding is performed using the same quantization width has many high-frequency components.
Compressing to a small code amount means that high frequency components are often truncated, which impairs image quality.However, an image with a small code amount is relatively impaired even if high compression is performed. By utilizing the property of no compression, a compression ratio suitable for each image is automatically set as described above.

[0047]

Embodiments of the present invention will be described below with reference to the drawings. First, to make the present invention easy to understand, a basic concept of the present invention will be described.

That is, the present invention first performs statistical processing by quantizing and encoding with the quantization width corrected by the provisional quantization width coefficient calculated corresponding to the target code amount as the first pass processing, The optimal quantization width coefficient is predicted, and the code amount to be allocated for each block is determined. And
A final encoding process is performed as a process of the second pass.
In the second pass, while quantizing the prediction quantization width coefficient for each block and encoding the same, the code amount of the block is set so that the code amount obtained by this encoding falls within the allocated code amount for each block. While monitoring
The coding is advanced, and when the code amount including the EOB code reaches the allocated code amount, the coding of the block is terminated and the coding of the next block is started. Also, in order to quickly converge to a value close to the target code amount, according to the target code amount that changes depending on the shooting mode such as the low image quality mode and the high image quality mode,
The function of giving a standard quantization width coefficient α that can obtain a code amount close to the code amount in the first pass is previously provided in the statistical processing system.

The statistical processing predicts the optimal quantization width and determines the allocated code amount for each block. The prediction of the optimum code amount coarsely reduces the code amount at the time of encoding (but considerably This is a process for approaching (with the accuracy of). By using this optimized quantum width in the encoding process,
It becomes possible to approximate the target code amount.
At this point, if the code amount falls within the target code amount, this processing alone is sufficient. However, if the upper limit of the data amount of one image is specified, let alone one byte, let alone one byte, The code amount cannot be exceeded. Therefore, a processing method when the overrun is required is required.

That is the determination of the allocated code amount for each block. This is for determining data to be used for fine adjustment when the code amount at the time of encoding exceeds the target code amount. Looking at the result of actually executing the encoding process at the optimal quantization width predicted in the statistical process, if it does not exceed, it may end, and if it does, it may be called post-processing. There are three steps: statistical processing, encoding processing, and post-processing. Not only is it time-consuming, but it is also necessary to save the encoding processing and post-processing so that codes of different lengths can be distinguished without joining them. Occurs, which is a problem, and it is desired to perform fine adjustment during the encoding process. However, dropping data indiscriminately leads to deterioration of image quality, and therefore must be avoided.

Therefore, in the present invention, visual effects are minimized by omitting high frequency components in each block. However, it is impossible to determine whether or not the code amount is exceeded until the coding is completed. Therefore, in the present invention, it is determined for each block.

This is the relative ratio of the generated code amount of each block to the code amount of each block generated when encoding is performed using the optimum quantization width or the quantization width predicted by statistical processing. However, since it has been confirmed by experiments that it does not change much, this is used. In other words, when performing encoding using a tentative quantization width (which can be estimated very coarsely depending on the target code amount) in the statistical processing, when the encoding is performed , the code amount of the entire image unless it exceeds this Do not exceed the target code amount ", and this guideline is used as a reference for monitoring as the allocated code amount for each block.

When the quantization width and the assigned code amount for each block are determined in this way, an encoding process is performed based on the quantization width and final encoding is performed. In the present invention,
In the encoding process, the encoding is terminated in each block so as not to exceed the allocated code amount of the block.

In the coding of each block, it is checked so as not to exceed the guideline (the amount of code to be allocated) while sequentially coding from low frequency components to high frequency components. Blocks that do not exceed the end of coding without any problem, that is, output EOB. In the block that has been exceeded in the middle, the higher frequency components are not coded, and the coding is terminated, and the coding of the block is terminated, that is, the EOB is output. At this time, since the EOB is one of the Huffman codes, it is necessary to include the EOB within the allocated code amount.

In this way, for example, if half of the blocks have completed encoding without having to be truncated, and the other half have omitted a part of the extremely high frequency and have completed encoding, the missing information will be lost. Is extremely small, and the missing information can be limited to information of high frequency components which have little visual influence. With this method, encoding can be always terminated in two steps of statistical processing and encoding processing, so that the total code amount can be kept within a specified value. Deterioration of image quality can be suppressed within the range.

An embodiment of the apparatus using the above principle will be described. FIG. 1 is a block diagram showing an embodiment of a digital electronic camera having a built-in image data encoding apparatus according to the present invention, and FIG. 2 is a block diagram showing the configuration of an image data encoding apparatus according to the present invention. The illustration and description of the mechanism of the digital electronic camera that is not directly related to the present invention is omitted.

As shown in FIG. 1, the electronic camera body 1 has an image pickup system 40 for picking up an image and an output of the image pickup system 40.
A signal processing circuit 60 that performs predetermined signal processing; and an encoding circuit 80 that has pre-processing, linear quantization, and entropy encoding functions, and that compresses and encodes the output of the signal processing circuit 60 and outputs the result.
And the image data encoded by the encoding circuit 80 and the quantization width (or information corresponding thereto) on a recording medium.
A recording system 70 for recording data on the switch 71, a switch 30 for setting and inputting a desired data compression ratio, and a control circuit for controlling the entire system
90.

The operation unit of the electronic camera body 1 is provided with a switch 30 for setting an image compression ratio.
Is connected to the control circuit 90.

The image pickup system 40 has a lens 40a for forming an optical image and an image pickup device 40b such as a CCD. The signal processing circuit 60 includes an amplifier 60 for performing amplification, noise removal, and the like.
a, an A / D converter 60b for converting an analog signal into a digital signal, a buffer memory 60c such as a RAM, and a process circuit 60d for forming color signals. Encoding circuit
80 includes, for example, an orthogonal transformation unit 4 for performing orthogonal transformation such as DCT (discrete cosine transformation), a quantization unit 6 for performing linear quantization, and a Huffman encoding unit 8 for performing Huffman encoding as entropy encoding. Width prediction unit 12, code amount calculation unit
14, code amount allocating unit 20, code truncating unit 16, and coding circuit
And a control circuit 18 for performing control processing in 80.

The recording system 70 comprises an interface circuit 70a and a memory card 71 containing an IC memory used as a recording medium. The memory card 71 is detachable from the electronic camera body 1. The control circuit 90 is realized by a microprocessor (MPU).

FIG. 6 is a perspective view showing the external appearance of the electronic camera body 1. The figure shows a binocular type, 48 is an LCD (liquid crystal) display in the operation unit, 30 is a switch 30 in the operation unit, and a tele-wide switch,
A shutter operation button 50 and the like are provided. 49 is a finder. Under the control of the control circuit 90, the LCD display 48 displays various values and states such as a shooting mode, the number of frames, date and time. In this electronic camera, the image compression ratio can be set to a desired value by operating the switch 30 provided on the operation unit of the electronic camera body 1. That is, standard plural types of compression ratio information are set in the control circuit 90 in advance, and based on the value of the number of recordable images set by the operation of the switch 30, this is set in the attached memory card (recording The compression rate to be applied is obtained from the capacity of the medium, and is converted into the value of the obtained compression rate and the value of the number of images that can be recorded on the memory card.
The display 48 displays the information. Then, when the user presses the switch 30, the control circuit 90 changes these values each time the switch 30 is pressed.

The user stops pressing the switch 30 at the desired value while watching the displayed change value, so that the control circuit 90 sets the designated compression ratio corresponding to the designated photographable image number designation value at that time. To be set. This is performed by the control circuit 90 obtaining a standard total code amount per image determined according to the compression ratio, and providing this to the encoding circuit 80 as target code amount setting information. Also, when the shutter operation button 50, which is a trigger switch, is pressed,
The shutter function is activated to form a subject image on the image sensor 40b, and a charge image corresponding to this image is accumulated in the image sensor 40b.
The video signal can be obtained from b. These controls are also controlled by the control circuit 90.

The image pickup system 40 shown in FIG.
And an image pickup device 40b composed of an image pickup device such as a CCD.
The optical image formed on the image sensor 40b by the photographing lens 40a is converted into an image signal and output to the signal processing circuit 60. The signal processing circuit 60 includes an amplifier 60a and an A / D converter
60b, a buffer memory 60c, and a process circuit 60d. An image signal obtained by the image sensor 40b by the process circuit 60d is a color signal Y, RY (hereinafter, RY is abbreviated as Cr (chroma red)). , BY (hereinafter, this BY is abbreviated as Cb (chroma blue)), and gamma correction and white balance processing are performed.

The output video signal of the imaging system 40, which has been digitally converted by the A / D converter 60b, is stored, for example, in a buffer memory 60c having a capacity of one frame, read out and sent to a process circuit 60d. Given, Y component and chroma (C; color difference signal) which are luminance signal system
The system is separated into Cr and Cb components. Buffer memory 60c
The image data stored in the image data is processed by a process circuit to obtain Y component data of the image signal, for example, in order to first perform statistical processing on a luminance signal, and the Y component is given to the encoding circuit 80. Encoding processing is performed on the data, and when the processing is completed, next, processing processing is performed on the data of the chroma Cr and Cb components, and then the encoding processing is performed.

The signal processing circuit 60 has a blocking function. The Y component and Cr and Cb component image data (for one frame or one field) read from the buffer memory 60c and processed. ) Can be divided into blocks of a predetermined size. Here, the block size is 8 × 8 as an example, but this block size is not limited to 8 × 8, and the block size may be different between Y and C (chroma system).

In this embodiment, the data of the luminance system Y is read out and divided into blocks, which are supplied to a subsequent processing system to perform statistical processing on the Y component data. In order to start the statistical processing for the data of the chroma Cr and Cb components, the data of the chroma Cr and Cb components is read out and blocked. In the chroma blocking, it is assumed that all the image data of the Cr component are firstly blocked, and then the image data of the Cb component is blocked.

The encoding circuit 80 has the configuration shown in FIG. In FIG. 2, reference numeral 4 denotes an orthogonal transformation circuit, which receives each image data which has been input as a block, and performs two-dimensional orthogonal transformation on the image data for each block. As the orthogonal transform, cosine transform, sine transform, Fourier transform, Hadamard transform and the like can be used.
By performing the orthogonal transform, image data as a transform coefficient is obtained.

Reference numeral 6 denotes a quantization circuit which receives the image data (transformation coefficient) output from the orthogonal transformation circuit 4 and outputs the first data.
In the first quantization, the transform coefficient is quantized with a quantization width corrected by multiplying a preset quantization width for each frequency component by a preset quantization width coefficient α according to the shooting mode. In the second time, the quantization is performed using the optimum quantization width coefficient α determined by the previous processing.

Reference numeral 8 denotes an entropy coding circuit. The entropy coding circuit 8 performs entropy coding (variable length coding) on the quantized output output from the quantization circuit 6. Huffman coding, arithmetic coding and the like are used as entropy coding. Since entropy coding is variable-length coding, the code amount of the entire code amount image for each block changes for each image. Although what kind of entropy coding is used is not directly related to the present invention, an example using Huffman coding will be described here.

The entropy encoding circuit 8 scans from the low frequency components to the high frequency components by a method called zigzag scanning in which the input quantized transform coefficients are scanned in the order shown in FIG. The data of the first DC component [DC] in the scanning order in FIG. 9 outputs a difference value from the DC component of the block on which entropy coding has been performed immediately before, by Huffman coding. Regarding the AC component [AC], the conversion coefficients are looked up in order from the second to the 64th in the scanning order in FIG. 9, and the conversion coefficient is not 0 (ie, (zero run) and the value of its effective coefficient are two-dimensional. The operation is to perform Huffman encoding and output.
If an invalid coefficient continues up to the 64th coefficient, an EOB (end of block) code indicating the end of the block is output. When the censor signal is input, the coding is terminated, and EOB is added and output. Then, the code amount generated for the block is output to the code amount calculation circuit 14.

The code amount calculation circuit 14 receives the input Y, Cr, Cb
The code amount for each block of each component and the integration of the code amount are performed, the code amount data for each block of each component of Y, Cr, and Cb are collected, and the code amount of the entire image is calculated. The data of the amount is output to the quantization width prediction circuit 12, and the data of the code amount of each block and the code amount of the entire image are output to the code amount allocating circuit 20.

At the start of the first pass, the quantization width prediction circuit 12 receives information on the target code amount from the control circuit 18,
From the code amount information, an initial value of the quantization width coefficient α is set by using the relationship of Expression (1) described later, and output to the quantization circuit 6,
Prior to the start of the second pass, the code amount of the entire image input from the code amount calculation circuit 14 and the target code amount which is the maximum allowable data amount per image are calculated based on, for example, Newton-Raphson Quantization width coefficient α that is optimal for approaching the target code amount using the Newton-Raphson iteration
Is predicted in consideration of the quantization width coefficient actually used this time.

The code amount allocating circuit 20 is a code amount calculating circuit.
Code amount of image data for each block input from 14,
The code amount assigned to each block is calculated from the code amount of the entire image and the target code amount, and the calculated code amount is output to the coding truncation circuit 16.

In this calculation method, the target code amount is proportionally distributed, for example, by the ratio of the code amount for each block. For example, the code amount of a certain block is multiplied by the target code amount, and the result is divided by the code amount of the entire image to determine the allocated code amount of the block. As a result, the code amount allocated to each block is appropriately suppressed when the code amount is small according to the actual code amount in the block, and the code amount allocated to the block with a large code amount is correspondingly large. Can be

The code amount allocating circuit 20 has a code amount information table and a block allocated code amount data table. The code amount information of the corresponding block position in the code amount information table is added to the code amount information input from the code amount calculating circuit 14. On the other hand, on the other hand, the allocated code amount of each block is calculated from the code amount of each block and the code amount of the entire image input from the code amount calculation circuit 14 and the target code amount, and the calculated allocated code of each block is calculated. The amount data is stored in the block allocation code amount data table.

The allocated code amount for each block in the block allocated code amount data table is supplied to the coding truncation circuit 16 when the corresponding block is subjected to entropy coding processing.

The coding truncation circuit 16 subtracts the code amount of each block from the code amount allocation circuit 20 from the allocated code amount, and the remainder of the allocated code amount is the total code amount of the code amount to be transmitted and the EOB code. When it becomes smaller, a function of outputting an abort signal and supplying it to the entropy encoding circuit 8 to terminate the encoding of the block is provided.

Therefore, the coding truncation circuit 16 refers to the allocated code amount, and inputs the code amount to be transmitted and the EOB
If the code amount does not exceed the allocated code amount even if the code is transmitted, the truncation is not performed, the coding of the block is terminated, and an operation of reducing the code amount to be transmitted from the allocated code amount of the block is performed. .

Reference numeral 10 denotes a code output circuit. The code output circuit 10 connects variable-length codes input from the entropy coding circuit 8, and connects the connected codes to a recording medium such as a memory card. It functions to write to the configured recording system 22.

In this system, statistical processing is first performed (first pass) using the standard quantization width coefficient α for the initial time determined according to the shooting mode, and the amount of information for each block necessary for optimization is obtained. And the amount of information of the entire image is checked, and then the process enters into a process for performing an optimized coding based on the information obtained by the statistical process (second pass).

Therefore, first, image blocking, quantization using the standard quantization width coefficient α for the elements of the blocked image, entropy coding of the transform coefficients obtained by quantization, and , Prediction of the coding width coefficient α required for obtaining the optimum code amount from the code amount information of each element of each block obtained by this entropy coding and the code amount information of the entire image, and the assigned code in each element of each block. Determination of the amount, transition to the processing mode of the optimal coding for the image to be processed based on these, the blocking processing of the image in the execution of this processing mode, the predicted quantization width α for the elements of the blocked image Procedures such as quantization processing used, entropy coding of transform coefficients obtained by this quantization, and output processing for storing all codes of the image to be processed. Thereby subjected, but it is assumed that the entire control management are to perform by the control circuit 18 in FIG. Note that such a function of the control circuit 18 can be easily realized by using a microprocessor (CPU). The above is the configuration of the encoding circuit 80.

The recording system 70 in FIG. 1 includes an interface circuit 70a and a recording medium 71 detachably connected to the interface circuit 70a. The image data encoded by the encoding circuit 80 and output and the quantization width (or The information corresponding to this is recorded on the recording medium 71 via the interface circuit 70a.

Next, the operation of the present apparatus having the above-described configuration will be described. First, the basic operation will be described with reference to FIG. When the camera user uses the camera, the user operates the switch 30 to set a desired number of recordable images. Thus, the control circuit 90 obtains the optimum code amount in accordance with the set number of recordable images, and supplies this to the encoding circuit 80 as target code amount setting information. Thus, the number of shootable images is set.

Next, when photographing is performed, a subject image is formed as an optical image on the image pickup device 40b placed behind the photographing lens 40a. The imaging device 40b converts the formed optical image into an image signal and outputs the image signal. Image sensor 40b
Is input to a signal processing circuit 60, where it is amplified by an amplifier circuit 60a in the signal processing circuit 60, and A / D
After A / D conversion by the converter 60b, the data is temporarily stored in the buffer memory 60c. Thereafter, the data is read from the buffer memory 60c, and the process such as band correction and color signal formation is performed by the process circuit 60d in the signal processing circuit 60.

Here, the following encoding processing is performed for Y (luminance),
Since the r and Cb (both color difference) signals are performed in this order, the color signal formation is also performed in accordance with this. That is, the image signal is read by being blocked in an 8 × 8 matrix, and the process circuit uses the blocked image signal data in the order of Y component, Cr component (RY component), and Cb component (BY component). These signals of each color component are separated, and gamma correction and white balance processing are performed.

8 × 8 separated by the process circuit 60d
The image signal data of each color component in the block image signal of the matrix is input to the encoding circuit 80. As a result, image data for one frame (or one field) is divided into blocks having the predetermined size and sequentially input to the encoding circuit 80. The process circuit 60
The image signal of each color component processed by d is Y, Cr, Cb
May be stored in the buffer memory for each component and read out and used in the subsequent processing.

In this embodiment, the Y component (luminance component) of the image signal data for one image is output from the signal processing circuit 60, and after the subsequent processing (statistical processing) for this is completed, Next, it is said that all blocking is performed on the image data of the Cr component, statistical processing is performed on the block at a later stage, and then the image of the Cb component is blocked, and the statistical processing is performed on the block at a later stage. Perform the following processing. The encoding circuit 80 supplies the input data received from the signal processing circuit 60 to the orthogonal transformation circuit 4.

Then, the orthogonal transform circuit 4 outputs the input image data which is divided into blocks (hereinafter, referred to as block image data).
For each block, for example, discrete cosine transform (DC
T) performs two-dimensional orthogonal transformation. The orthogonal transform by DCT is a process of dividing a certain waveform into frequency components and expressing this by the number of cosine waves equal to the number of input samples.

The orthogonally transformed block image data (transformation coefficients) are stored in a buffer memory (not shown) in the buffer memory.
It is stored in the corresponding frequency component position on the × 8 matrix (the matrix origin position is a DC component, and the other components are AC components, and are stored in a matrix that has a relationship such that the frequency increases with distance from the origin position) Are input to the quantization circuit 6.

Then, the quantization circuit 6 performs the first pass (first pass) quantization on the block image data (transform coefficients). In the first quantization, an image quality set value set by a user upon photographing is applied to a predetermined quantization matrix for each frequency component (frequency components are determined corresponding to each matrix position of a block). The quantization of the transform coefficient is performed by the quantization width obtained by multiplying the standard (temporary) quantization width coefficient α given by the control circuit 18 in correspondence with the processing (FIG. 8).
(h1, i)). The quantization matrix at this time may be the same for each of the luminance system and the chroma system. However, better results can be obtained by setting appropriate quantization matrices.

The quantized block image data (transformation coefficient) is input to an entropy encoding circuit 8, where
Entropy coded. Entropy coding circuit 8
Then, the quantized and inputted transform coefficients are zigzag-scanned in the order shown in FIG. 8 to scan from low frequency components to high frequency components. That is, the transform coefficients are stored in a 8.times.8 matrix corresponding to the frequency components. Since the frequency is lower as the position is closer to the origin, zigzag scanning enables scanning from a lower frequency component to a higher frequency component.

Since the first data in the scanning order in FIG. 9 is the DC component DC, the data of this DC component DC is the block (the immediately preceding block) on which entropy coding was performed immediately before.
The difference value diff-DC from the DC component DC is subjected to Huffman coding (FIGS. 8 (d1) and (e1)).

The AC component AC is the same as that in the scanning order shown in FIG.
Look at the transform coefficients in order from the 64th to the 64th, and if a transform coefficient that is not 0 (ie, valid) comes out, the number of consecutive 0 (invalid) coefficients that existed immediately before (zero run) and Two-dimensional Huffman coding is performed with the value of the effective coefficient ((d2), (e2)).

Further, the entropy encoding circuit 8 gives an EOB (end of block) code indicating the end of a block when an invalid coefficient continues from a certain coefficient up to the 64th coefficient.

Then, the code amount generated for the block is output to the code amount calculation circuit 14 (g1). Then, such processing is executed for all blocks of one image.

When such processing for the Y component is completed, similar processing is performed for each of the Cr and Cb components. On the other hand, the code amount calculation circuit 14 calculates Y, Cr, and Cb in order to calculate the code amount of one input image of each of the input Y, Cr, and Cb components.
The calculation of the code amount of each block of each component and the integration of the code amount are performed (g2), and the data of the code amount of each block is output to the code amount allocation circuit 20. The code amount allocating circuit 20 writes the code amount data for each block as code amount information of the corresponding block position in the code amount information table.

Then, for all blocks of one image
At the stage where the Huffman encoding process for all the Y, Cr, and Cb components is completed, the code amount calculation circuit 14 is controlled by the control circuit 18.
Is the quantization width prediction circuit
In addition to outputting to the code amount data, the code amount data of the entire image is output to the code amount assignment circuit 20.

The quantization width prediction circuit 12 uses the input code amount data of the entire image and the target code amount data by using, for example, the Newton-Raphson iteration method to optimize the code amount close to the target code amount. The quantization width coefficient α is predicted based on the actually used quantization width coefficient (FIG. 8 (h2)).

The code amount allocating circuit 20 determines the allocated code amount of each block from the input code amount of each block, the code amount of the entire image, and the target code amount, for example, the ratio of the code amount of each block. Then, the target code amount is calculated by, for example, proportional distribution (FIG. 8 (h3)). Specifically, to determine the allocated code amount of a block, the code amount of the block is multiplied by the target code amount, and the result obtained by dividing the result by the code amount of the entire image is used as the allocated code amount. I do. Then, the data of the calculated allocated code amount of each block is stored in the block allocated code amount data table. The data of the allocated code amount for each block in the block allocated code amount data table is as follows:
When the corresponding block is subjected to the entropy coding process, the block is supplied to the coding truncation circuit 16.

Thus, the first pass, that is, the first coding (statistical processing) for determining the amount of code to be allocated to each block and optimizing the quantization width is completed.

Next, the process enters the second pass. The processing of the second pass is the second encoding (encoding processing), and is the processing of obtaining the final encoded output optimized to be within the target code amount.

This processing is first performed for the Y component.
After the completion of the components, the process is performed for the Cr and Cb components. That is, first, the image data is divided into blocks and read out, and the Y-component (luminance-based) image signal data extracted and output from the signal processing circuit 60 is encoded.
(A). The input block image data is input to the orthogonal transform circuit 4 in the encoding circuit 80, and the orthogonal transform is performed again (b). The transform coefficient obtained by the orthogonal transform is input to the quantization circuit 6, where the quantization is performed again (c). However, the quantization width coefficient α used at this time is the optimum quantization width coefficient α for the prediction calculated by the quantization width prediction circuit 12 in the previous pass.

Next, the quantized transform coefficients of the block image data are input to the entropy encoding circuit 8. In the entropy coding, as in the case of the statistical processing, the difference value of the DC component DC is first included in the conversion count of the block image data.
The diff-DC is Huffman-coded ((d1), (e1)), and the AC component AC is sequentially extracted by zigzag scanning to perform two-dimensional Huffman coding ((d2), (e2)).

However, every time a Huffman code is generated for one element (one position in the matrix), the code amount allocation circuit 20 should transmit the data at the element position stored in the block allocated code amount data table. The allocated code amount is output to the coding truncation circuit 16. On the other hand, the coding truncation circuit 16 outputs the code amount to be transmitted and the EOB code even if the code amount of EOB is transmitted based on the allocated code amount of each block. If the value does not exceed the threshold value, a process of reducing the code amount to be transmitted from the allocated code amount of the block is performed without generating the truncation signal. Then, when the total code amount of the code amount of the block to be transmitted and the code of the EOB exceeds the remaining code amount of the allocated code amount, the coding truncation circuit 16 sends the truncation signal to the entropy coding circuit 8. Is output, and Huffman coding of the block is terminated. Then, the entropy coding circuit 8 shifts to the Huffman coding of the next block obtained from the quantization circuit 6.

Therefore, the entropy encoding circuit 8 outputs the converted Huffman code to the code output circuit 10 until the truncation signal is input from the encoding truncation circuit 16, and outputs all the elements of the matrix before the truncation signal is generated. Is completed, the entropy encoding circuit 8 outputs the code of EOB to the code output circuit 10. Also,
If a truncation signal is input before Huffman coding for all elements of the matrix is not completed, the entropy coding circuit 8 outputs a code of EOB to the code output circuit 10 instead of the code.

The code output circuit 10 temporarily stores the encoded data. Then, the entropy encoding circuit 8
Shifts to Huffman coding of the next block obtained from the quantization circuit 6.

By repeating the above operation, the processing of all the blocks of the image of one screen is completed, thereby completing all the encoding processing. After such processing for the Y component is completed, processing for chroma-based components (Cr, Cb) is started in a similar manner. The quantization circuit 6 uses the optimum quantization width coefficient α of the prediction calculated by the quantization width prediction circuit 12 in the previous pass also in the processing of the chroma component.

As for the chroma components, the processing of the second pass for all the blocks of the image for one screen is completed.
All encoding processing ends. At the end of this, the code output circuit 10 outputs the optimized Huffman coded data for one image to the recording system 22 and writes it to a storage medium 71 such as a memory card in the recording system 22 (f). This is performed by the output of the code output circuit 10. The code output circuit 10 writes by connecting the variable-length Huffman codes from the entropy coding circuit 8 to give to the memory card as the storage medium 71.

A storage medium based on the output of the code output circuit 10
Writing to 71 may be performed collectively at the end of the second pass, but the result of joining variable-length Huffman codes at the end of the first pass and execution of the second pass may be obtained. The data may be written to the storage medium sequentially in units of one byte or several bytes as soon as they are collected. still,
Prior to this, the code output circuit 10 writes the optimum quantization width coefficient α used for coding in the header portion of the storage data of the coded image and leaves it as a clue at the time of reproduction.

As described above, in the present apparatus, when the image quality is designated by selecting the number of recordable images, the provisional quantum amount corresponding to the total code amount per target image (target code amount) determined according to the designated image quality is determined. The calculated quantization width is calculated, statistical processing is performed using the calculated provisional quantization width (first pass), an optimum quantization width is predicted based on the data, and then the predicted quantization width is calculated. Using the quantization width, quantize and encode it to obtain the final encoded image data (second pass)
Thereby, the code amount in the encoding process is made closer to the target code amount, and the code amount in the encoding process is prevented from exceeding the target code amount by further determining the assigned code amount of each block. This is an important point of the present invention.

Therefore, the present invention is not limited to the block size, the type of orthogonal transform, the type of entropy coding, and the like used in this embodiment. Further, the image data buffer memory may be provided between the orthogonal transformation circuit 4 and the quantization circuit 6, and in this case, the processes of blocking and orthogonal transformation in the encoding process can be omitted. However, in order to maintain accuracy, the size of the image memory is increased in this case. Also, the processing may be performed before the A / D conversion and digitized thereafter. Further, in the present apparatus, entropy coding for each block is performed from the low-frequency component side, and high-frequency components having a relatively small effect on image quality are coded and used within a range where the allocated code amount has a margin. Therefore, it is possible to perform encoding with high compression while minimizing deterioration of image quality.

The present invention having the configurations shown in FIGS. 1 and 2 described above is, in short, a quantization width close to the optimum quantization width set from the target code amount as the provisional quantization width for the first pass. To perform a first pass quantization, and as a result, further optimize a quantization width using the obtained code amount data,
This is used for the encoding in the second pass which is the final processing. This is based on the fact that, when statistical processing is performed using a quantization width coefficient α that provides a code amount close to the target code amount, the optimum quantization width coefficient α can be found quickly and more accurately. The first pass quantization is performed using a quantization width coefficient close to the optimum quantization width set based on the target code amount as a provisional quantization width coefficient, and the target code amount is calculated based on the total code amount thus obtained. Knowing the quantization width coefficient that can be contained in the code amount,
This is used in the pass to perform final encoding.

Thus, the image data obtained by the imaging system by shooting can be coded in a short time and with high accuracy and in the entire frame of the target code amount, so that the code amount can be brought close to the allowable code amount as much as possible. Thus, lost data is kept to a minimum and the image quality can be maintained, so that the prediction accuracy is high and the image quality is hardly degraded due to encoding, that is, high-quality quantization can be performed.
In addition, even if the target code amount changes, the same hardware can cope with the change. Therefore, it is not necessary to prepare hardware for each target code amount (for each compression ratio), so that the cost and size of the apparatus can be reduced.

Here, how to set the provisional quantization width coefficient to an optimum value is an important issue, and this point will be described briefly. It is a well-known fact that when image data is pre-processed, this output is quantized, and when this quantized output is subjected to variable-length encoding, the generated code amount changes by changing the quantization width of this quantization. It is. This is because variable-length coding represented by Huffman coding reduces the amount of code required to represent the data using the bias in the probability of occurrence of the data to be coded. Since "changing the quantization width" means changing the probability of occurrence of the quantization value, it can be seen that changing the quantization width also changes the generated code amount.

By the way, even if the same encoding is performed with the same quantization width, the generated code amount differs depending on the image data at that time. However, when the same encoding is performed by changing the quantization width for one image data, a fixed relationship is obtained between the quantization width and the generated code amount. In addition, when the relationship between the quantization width and the generated code amount is obtained for many pieces of image data, it has been found that the relationship having the highest frequency of occurrence can be obtained statistically.

Specifically, in many cases, the following relationship was obtained. That is, assuming that a relative ratio with respect to a certain quantization width is SF, which is represented by the number of bits per one pixel (bit rate) of generated code amount and is BR, log BR = a × log SF + b (1) It becomes a relationship. If a is the same encoding, it is substantially constant regardless of the image, and b depends on the image. The value of b has a certain distribution depending on the image, and a representative b can be obtained from the occurrence frequency distribution.

In the above, an example has been described. In any case, the feature of the present invention is that the quantization width is set in accordance with the target code amount by utilizing the relationship between the quantization width and the code amount. There.

The encoding circuit 80 having the configuration shown in FIG. 2 performs a series of processes in the first pass with a provisional quantization width calculated based on the target code amount in the compression encoding. The optimum quantization width is obtained in advance, the second pass is performed using the optimum quantization width, and the processing is completed by two processes of obtaining the final compressed and encoded data. It is to find out. In FIG. 3, the signal flow in the first pass is indicated by a dotted arrow P1,
The signal flow in the second path is shown by a solid arrow P2. The following is a brief description of the operation following the flow of this signal.

When the image data is encoded, the target total code amount is set in the control circuit 18 of the encoding circuit 80. This is because, by operating the switch 30, the user sets the desired number of shootable images, and the control circuit 90 selects the optimum code amount according to the set number of shootable images.
This is realized by giving this to the encoding circuit 80 as information on the target code amount. Note that in the initial state, the standard number of recordable images is set in advance.

When the photographing is performed, an image signal is output from the image pickup device in the image pickup system 40. The output image signal is converted into a digital signal in the signal processing circuit 60, stored in the buffer memory, read out in block units of 8 × 8 pixels, and read out from the Y component, then the Cr component, and then the Cb component. Separated into components. This separation is first performed for the Y component, and the image data of the Y component output in block units of 8 × 8 pixels is input to the orthogonal transform circuit 4 and orthogonally transformed (DCT; discrete cosine in this example) for each block. Conversion (Dis
crete Cosine Transform); prediction coding (DPCM may be used). The DCT transform coefficients obtained by the orthogonal transform circuit 4 are input to the quantization circuit 6, while
The control circuit 18 determines that the target code amount is the quantization width prediction circuit 12.
The quantization width prediction circuit 12 sets an initial value of the quantization width coefficient α from the target code amount using the relationship of the equation (1) and outputs the initial value to the quantization circuit 6. The quantization circuit 6 linearly quantizes the transform coefficient using the input quantization width coefficient α. The quantized transform coefficients are input to the entropy coding circuit 8, where variable length coding (Huffman coding in this example) is performed.

The input quantized coefficients are scanned from a low-frequency component to a high-frequency component, called zigzag scan, and the first DC component data is the data of the block immediately before the variable-length coding. The difference value from the DC component is Huffman-coded and output.

For the AC component, from the second in the scanning order
The conversion coefficients are examined in order up to the 64th, and if a conversion coefficient that is not 0 (ie, valid) comes out, the number of consecutive 0 (zero; invalid) coefficients that exist immediately before (zero run) and Two-dimensional Huffman coding is performed with the value of the effective coefficient. Also, after a certain coefficient, up to the 64th coefficient,
If invalid output continues, an EOF (end of file) code indicating the end of the block is output.
The variable length coding circuit 8 outputs the code amount generated in each block to the code amount calculation circuit 14 each time the above-described coding is completed in each block.

When such processing for the Y component is completed, the same processing is performed for the Cr component and the Cb component. When encoding of one image is completed, the code amount calculation circuit 14 accumulates the input code amount of each block and calculates the code amount of the entire image as a total code amount value. This total code amount value is output to the quantization width prediction circuit 12, and is also output to the code amount allocation circuit 20 for the code amount of each block and the entire image.

When the above-described first pass encoding process is completed, the second pass encoding process is subsequently performed on the same image data. In the second pass, the image data read from the memory in the signal processing circuit 60 is first Y component, then Cr
Component, and then into Cb components, and image data of each component is subjected to processing such as blocking of 8 × 8 pixels.
The signal is input to the orthogonal transformation circuit 4 and orthogonal transformation (DC
T transformation), thereby obtaining the orthogonal transform
The DCT transform coefficient is input to the quantization circuit 6.

On the other hand, in the quantization width prediction circuit 12, the total image code amount obtained by the encoding in the first pass and the control circuit 18
And a more suitable quantization width coefficient α is predicted from the target code amount given from the above and output to the quantization circuit 6. The quantization circuit 6 linearly quantizes the DCT transform coefficient using the corrected quantization width based on the given new quantization width coefficient α based on the prediction. The quantized coefficients are input to the variable length coding circuit 8, and are subjected to Huffman coding in the same manner as in the first pass coding.

Here, the code amount generated at the time of encoding is obtained at the time of the encoding of the first pass, and is compared with the allocated code amount of each block stored in the code amount allocating circuit 20, and exceeds the amount. In such a case, the subsequent coding is terminated in the block by the function of the code discontinuing circuit 16. The coded data controlled to the target code amount by the above method is sequentially
The data is output to the recording system 70 via the code output circuit 10 and recorded.

Next, reproduction of the compression-encoded recording image data of the recording medium 71 recorded by the recording system 70 will be described. FIG. 4 shows the configuration of the playback device. Referring to FIG. 1, reference numeral 100 denotes a reproducing apparatus main body, which includes a reading section 102, a decoding circuit 104, a processing circuit 106, and a control circuit 108. The reading unit 102 can attach and detach the storage medium 71, and reads the contents of the storage medium 71 via the interface circuit 110.

The decoding circuit 104 has functional blocks as shown in FIG. That is, reference numeral 112 denotes a Huffman decoding unit for decoding Huffman-coded data, and 114 denotes the Huffman-decoded data read out from the storage medium 71 based on the quantization width information read and set and input. An inverse quantization unit 116 for performing quantization performs inverse DCT conversion on the data obtained by the inverse quantization and outputs an IDCT (inverse
A DCT transform section 118 is a control section that controls these controls.

The processing circuit 106 includes a buffer memory 120, an encoder 122, and a D / A converter 124. The buffer memory 120 is a memory for temporarily storing the video signal data output from the decoding circuit 104, and the encoder 122 stores the video signal data read from the buffer memory 120.
Converts to NTSC video signal, D / A converter
Reference numeral 124 is for converting the NTSC video signal into an analog signal and outputting it as a TV video signal.

The control circuit 108 controls the entire reproduction apparatus main body 100. The control circuit 108 controls the reading section 102 of the reproduction apparatus main body 100 to read the information of the quantization width at the time of encoding. Then, the information of the quantization width at the time of encoding read from the recording medium 71 is set in the inverse quantization unit 114 of the decoding circuit 104, and then the control circuit 108 controls the video signal compressed and encoded from the recording medium 71. In order to read the data, control for controlling the reading unit 102 is performed. Although not shown, the playback device main body 100 has a frame feed switch or the like, and can reproduce a video at a frame position designated by the switch. The control circuit 108 also performs such control.

Next, the operation of the reproducing apparatus having the above configuration will be described.
When the recording medium (memory card) 71 on which the compression-encoded video signal data is recorded is mounted on the reading unit 102 of the playback device main body 100, first, the control circuit 108
Control is performed to read out information on the quantization width at the time of encoding. As a result, in the reading unit 102, information on the quantization width at the time of encoding is read from the recording medium 71, and this information is
4 is set to the inverse quantization unit 114. Subsequently, the control circuit 108
Controls the reading unit 102 to read the video signal from the recording medium 71, so that the reading unit 102 sequentially reads the video signal from the recording medium 71 and inputs the video signal to the decoding circuit 104. Upon receiving this, the decoding circuit 104 decodes the Huffman code in the Huffman decoding unit 112 to obtain a quantized coefficient. The quantized coefficients thus obtained are supplied to an inverse quantization circuit 114 for inverse quantization. Here, the inverse quantization is performed by using the information of the quantization width previously set.

The transform coefficient obtained by the inverse quantization is IDCT
In the section 116, the inverse DCT is performed for each block, and the original video signal is restored. In this way, the video signal is restored in the order of Y, Cr, and Cb, output from the decoding circuit 104, and written into the buffer memory 120 in the processing circuit 106. When the writing of the video signal data for one screen is completed, the video signal data is read out from the buffer memory 120 in the normal scanning order of the television signal, and is converted into the NTSC video signal by the encoder 122. Further, the signal is converted into an analog signal by the D / A converter 124 and output. By inputting this video signal to a television monitor, the image is reproduced as a television video and can be viewed as a video.
Since the hard copy is obtained, it can be viewed in the same manner as a photograph or the like.

As described above, the camera can set a desired number of recordable images, and by setting the number of recordable images, the camera automatically sets the corresponding compression ratio,
Using the provisional quantization width determined according to the set compression ratio, the captured image data for one screen is quantized and entropy-encoded, and the optimal code amount is obtained from the code amount of the captured image data for one screen obtained as a result. A quantization width is predicted, the captured image data for one screen is quantized by the predicted optimal quantization width, and entropy encoding is performed. When reproducing an encoded video signal, the optimal quantization used at the time of photographing is reproduced. By decoding using the compression width, encoding at a desired compression rate can be realized with one common hardware without providing hardware for each compression rate, and similarly, encoding at a desired compression rate can be performed. Decoding of image data can be realized by one common hardware without providing hardware for each compression ratio.

In the above-described embodiment, the two-pass method is used in which the encoding process is completed in two processes of the first pass and the second pass. In practice, even a method of encoding in one pass using
The compression ratio can be controlled sufficiently. Also, an example using a memory card as a recording medium has been described, but in addition, a floppy disk,
Optical disks, magnetic tapes and the like can also be used. Although the camera and the playback device are shown as being separated from each other, the camera and the playback device may be of an integrated type having the functions of the playback device. Although the quantization width value itself is recorded on the recording medium, the quantization width value may be converted or encoded and recorded. Preprocessing encoding is KL conversion, DPC
M conversion may be used. Entropy coding is arithmetic coding,
Run-length coding or the like may be used.

According to the present invention, the final target code amount of an image is automatically varied by setting the number of images that can be taken, and when the final target code amount is set, it is necessary to obtain the code amount. The point is that the quantization width coefficient α is calculated from the target code amount and is used for encoding. By paying attention to the fact that a code amount close to the target code amount can be obtained from the beginning, the quantization width coefficient α is approximately calculated in one pass. It can be an optimal value. This example is shown.

In this example, the encoding process of the first pass is performed only once, and the optimum value is obtained only in the first pass. FIG. 7 shows the configuration. In this example, the same components as those in the above-described embodiment are denoted by the same reference numerals, and description thereof will be omitted.

In the present system, when an arbitrary image quality setting value is given to the control circuit 18a, encoding is performed using a standard quantization width coefficient α determined in accordance with the image quality setting value. A), the quantization width prediction circuit 12 calculates a standard quantization width coefficient α from the target code amount provided from the control circuit 18a, and supplies the standard quantization width coefficient α to the quantization circuit 6, and the quantization circuit 6 Numeral 6 performs linear quantization with the quantization width corrected by the set quantization width coefficient α. The quantized transform coefficients are entropy-encoded by an entropy encoding circuit 8 and output to a code output circuit 10. Then, the encoded output is sent from the code output circuit 10 to a recording system and recorded on a recording medium.

Even when encoding is performed in a single pass as in the above example, the quantization width is set based on the target code amount, so that the quantization width approaches the optimum quantization width. It is possible to make the code amount to be approximately equal to the target code amount. In this case, since the processing is completed in one time, encoding can be performed at an extremely high speed.

In each of the above embodiments, the quantization width is set based on the target code amount. However, in an application in which a plurality of target code amounts are switched between modes, the quantization width corresponding to each mode is used. Prepare in advance,
Of course, it can be used by switching between modes.

According to the present invention, even if the target code amount is changed, an optimum quantization width for making the generated code amount close to the target code amount can be obtained. By performing quantization using this quantization width, the obtained code amount can be made close to the target code amount even when the coding is completed only by one coding process (one-pass method). In the two-pass method in which the code amount is controlled in the first encoding process, the quantization width is corrected based on the code amount obtained using the temporary quantization width in the first encoding process (statistical process). Therefore, it has the effect of improving the prediction accuracy of the optimal quantization width, can perform high-quality encoding, and can perform encoding processing until the total code amount is sufficiently close to the target value and is within the target code amount. An n-pass method that repeats the prediction of the optimal quantization width can be used. In this method, in the encoding process (statistical process) in the first pass,
The number of repetitions (until the quantization width converges to the optimum value) until finding the optimum quantization width for keeping the code amount within the target value is reduced, and the effect that the processing time required for encoding is reduced is obtained. .

The present invention is not limited to the embodiments described above and shown in the drawings, but can be appropriately modified and implemented without departing from the scope of the invention. The present invention is not limited to still images. The present invention can be applied to compression encoding of various images such as moving images.

Further, in the above embodiment, information of the total code amount is given from the compression ratio correspondence information, and a quantization width coefficient capable of giving a quantization width corresponding to the total code amount is predicted. Although the quantization is performed with the quantization width based on the quantization width coefficient, the relationship between the quantization width and the compression ratio correspondence information is calculated in advance and stored in a table, and this is stored in a memory or the like. It is also possible to output quantization width information (that is, quantization width coefficient or quantization width value) directly from the compression ratio correspondence information. In this way, when the information corresponding to the desired compression ratio is input, the information of the quantization width uniquely determined corresponding to the input compression ratio corresponding information can be read and output, and the optimum quantization can be immediately performed. As soon as the width can be set, the quantization circuit can quantize the image signal data with this quantization width.

According to this configuration, information on the optimum quantization width corresponding to various compression ratios is stored in advance in a memory or the like, and is read out in accordance with the input compression ratio correspondence information. Can be given, so that the encoding process can be performed in an extremely short time and the hardware can be simplified when encoding to the target code amount.

Next, still another embodiment of the present invention will be described.
In this example, the image quality can be automatically set without manually setting the image quality. That is, in this example, encoding is performed using the provisional quantization width, and the optimal image quality mode is set using the code amount generated at this time. In general, when encoding using the same quantization width, an image in which a large amount of code occurs has many high-frequency components, and high compression, that is, compressing this to a small amount of code, This means that high-frequency components are often cut off, which impairs image quality.

On the other hand, the quality of an image with a small amount of code generation is not relatively deteriorated even if high compression is performed. This embodiment utilizes this property and automatically sets a suitable compression ratio for each image.

FIG. 11 shows the configuration of the encoding circuit of this embodiment. The same components as those in the above-described embodiment are denoted by the same reference numerals, and description thereof will be omitted. In this embodiment, when taking a picture,
This image (digitized image) is divided into blocks, and then DCT is performed on each block in turn.
The DCT coefficient data for each frequency component is quantized using a temporary quantization width coefficient α for each frequency component in order from the low frequency component, and this is Huffman coded. The optimal target code amount is determined from the total code amount generated by the above and the code amount for each block, and the target code amount is distributed by the generated code amount for each block to determine the allocated code amount for each block. Determine the optimal quantization width for each frequency from the total code amount obtained and the target code amount, perform blocking of the image obtained by the shooting, and then perform DCT on each block in order to obtain coefficients for each frequency component, The DCT coefficient data for each frequency component is sequentially converted from the low frequency component to the optimal quantization width coefficient α for each determined frequency component.
Is performed using Huffman coding, and the generated code is recorded within a range not exceeding the allocated code amount in the block. abort.

The control circuit 90 has a control function for performing such processing. Then, first, the control circuit 90 is caused to determine the target code amount most suitable for the image being processed from the value of the total code amount at the time of the statistical processing (the value of the total code amount generated in the processing of the first pass), The target code amount determined by the control circuit 90 is set in the control circuit 18, and the control circuit 18 instructs the quantization width prediction circuit 12 from the determined target code amount and the total code amount at the time of the statistical processing. The optimal quantization width coefficient α for each frequency component is controlled to be predicted, and the optimal quantization width for each frequency component obtained by correcting with the predicted optimal quantization width coefficient α for each frequency component is calculated. Quantization width prediction circuit 12
Thus, the quantization data is supplied to the quantization circuit 6 so that the quantization circuit 6 quantizes the image data (DCT transform value) for each block with the optimum quantization width for each frequency component.

The quantized output is supplied to an entropy coding circuit 8, and the generated code is coded so as to be within the allocated code amount of the block. The coding in the block is discontinued so that the code amount falls within the range of the allocated code amount.

In such a configuration, when photographing is performed, an image signal is output from the image pickup device in the image pickup system 40.
The image signal output from the imaging system 40 is converted into a digital signal in the signal processing circuit 60, and is read out in blocks of 8 × 8 pixels. The image data of the digital signal read in block units is input to the encoding circuit 80. The image data input to the encoding circuit 80 is first subjected to DCT for each block by the orthogonal transformation circuit 4 in the encoding circuit 80, and the DCT which is a value for each frequency component is obtained.
Get the coefficients. Then, the quantized circuit 6 in the encoding circuit 80 performs linear quantization on the obtained DCT coefficient by using a preset provisional quantization width for each frequency component. . The quantized transform coefficients are subjected to Huffman coding by the entropy coding circuit 8 in the coding circuit 80.

On the other hand, the code amount calculation circuit 14 in the coding circuit 80
Calculates the code amount of the coded image data based on the output of the entropy coding circuit 8 and outputs it to the code amount allocating circuit 20. The code amount allocating circuit 20 in the encoding circuit 80 stores the generated code amount for each block.

Such processing is sequentially performed for each block under the control of the control circuit 90. When the processing of the block for one screen is completed, the total code amount generated for the one screen is sent from the code amount calculation circuit 14 to the quantization width prediction circuit 12 and the control circuit 90 in the coding circuit 80. Output. The control circuit 90 determines a target code amount most suitable for the image being processed from the value of the total code amount, and sets it in the control circuit 18.

Thereafter, under the control of the control circuit 90, the signal processing circuit 60 starts the encoding processing which is the processing of the second pass. This is started by reading out the image data from the buffer memory 60c again, performing block processing, and inputting the block data to the encoding circuit 80. The encoding circuit 80 supplies the input image data to the orthogonal transform circuit 4, performs DCT by the orthogonal transform circuit 4, and supplies the obtained DCT coefficients to the quantization circuit 6.

On the other hand, the quantization width prediction circuit 12 of the encoding circuit 80
In the first pass, a more suitable quantization width coefficient α for each frequency component is predicted from the obtained total image code amount and the target code amount by the encoding in the first pass, and this predicted value is Output to Further, the code amount allocating circuit 20 determines an allocated code amount for each block by proportional distribution from the stored code amount for each block and the target total code amount from the control circuit 90, and stores this. .

The quantization circuit 6 uses the corrected quantization width obtained by multiplying the given quantization width coefficient α for each frequency component by the weight for each frequency component given by the quantization matrix. Then, the DCT transform coefficients output from the orthogonal transform circuit 4 are linearly quantized in order from a low frequency region.

The linearly quantized coefficients are Huffman-coded by the entropy coding circuit 8. Here, the code amount generated at the time of the encoding process which is the process of the second pass is obtained at the time of the above-mentioned provisional encoding (at the time of encoding at the statistical process which is the process of the first pass). A comparison is made with the allocated code amount of each block stored in the amount allocation circuit 20. If the amount exceeds this, the code discontinuation circuit 16 instructs the entropy encoding circuit 8 to terminate the encoding. As a result, the encoding process of the block being encoded in the entropy encoding circuit 8 is discontinued, and the subsequent encoding is discontinued in the block. The command to terminate the encoding is also sent to the control circuit 90, and the control circuit 90 shifts to the above-described encoding processing control for the next block.

The encoded data controlled to the target code amount by the above method is sequentially output to the recording system 70 via the code output circuit 10 and recorded.

As described above, in the first encoding (processing in the first pass), that is, in the encoding at the time of statistical processing, which is encoding using a provisional quantization width coefficient, the orthogonal transform value for each block is used. Is subjected to variable-length coding using a provisional quantization width coefficient determined for each frequency component, and the generated total code amount by the provisional quantization width coefficient for one captured image is calculated. The amount of code at which the optimal compression rate does not impair image quality is determined and set as the target code amount, and the optimal quantization width coefficient for each frequency component is determined from the target code amount and the code amount generated during the statistical processing. At the time of the encoding process (the process in the second pass), the orthogonal transform value for each block is encoded with the quantization width coefficient determined for each frequency component, and the allocated code amount for each block is not exceeded. Proceed with encoding and exceed the allocated code amount The case truncation coding in the block. Thus proceeds to encode the next block,
A compression ratio suitable for each image can be automatically selected.

That is, since the code amount output from the encoding circuit is used as a criterion for selecting the compression ratio, no special circuit is required for selecting the compression ratio. Further, it is possible to control various target code amounts with the same hardware.

In this system, Y as in the previous embodiment is used.
(Luminance) component, C (chroma) component (C component is further Cr, Cb
(It is also possible to subdivide into color components). In addition, since the target code amount has a standard of the minimum recordable number of recording media, there is a method in which several selectable target code amounts are determined in advance, and a value considered to be optimal from the generated code amount is used. Optimal.

[0160]

As described in detail above, according to the present invention,
Compression encoding of images can be performed at a desired compression ratio. Even if the compression ratio changes, compression encoding can be realized with one shared hardware, not by compression ratio, and the reproduction system can also be compressed. It is possible to reproduce with one common hardware, not rate, and to obtain a compressed code amount close to this code amount corresponding to the target code amount, and to obtain the best image quality in the range of the target code amount Thus, it is possible to provide an electronic camera system in which image quality does not deteriorate and hardware cost can be reduced and the size can be reduced. According to the present invention,
For example, after separating a video signal into a luminance signal component and a chrominance signal component,
Then, using the quantization width information corresponding to each of these components,
Since the encoding process is performed, the quality of the reproduced image is improved.
Can be compressed to a small amount of information while maintaining
An electronic camera that has a large number of images that can be taken
An apparatus can be provided. Also, the information of the quantization width is
By recording on a recording medium, this quantization
Easy and quick image playback using width information
Become.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a first embodiment of the present invention.

FIG. 2 is a block diagram showing a configuration example of a main part of the apparatus of the present invention.

FIG. 3 is a block diagram for explaining an operation flow of the circuit of FIG. 2;

FIG. 4 is a block diagram showing a configuration of a playback device.

FIG. 5 is a block diagram showing a configuration of a playback device.

FIG. 6 is a perspective view showing the appearance of an electronic camera body according to the present invention.

FIG. 7 is a block diagram illustrating a configuration example of an encoding circuit in the case of a one-pass method.

FIG. 8 is an operation transition diagram for explaining the principle operation of the present invention.

FIG. 9 shows a zigzag pattern of a block divided into 8 × 8 pixels.
FIG. 4 is a diagram for explaining scanning.

FIG. 10 is an operation transition diagram for explaining a conventional technique.

FIG. 11 is a block diagram showing another embodiment of the present invention.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Electronic camera main body, 6 ... Quantization circuit, 8 ... Entropy coding circuit, 10 ... Code output circuit, 12 ... Quantization width prediction circuit, 14 ... Code amount calculation circuit, 16 ... Code termination circuit, 18, 18a
... control circuit, 20 ... code amount allocation circuit, 24 ... DCPM circuit, 30 ...
Switch, 40: imaging system, 48: LCD display, 60: signal processing circuit, 80: encoding circuit, 70: recording system, 71: recording medium, 90
... Control circuit, 100 ... Reproducer body, 102 ... Reading unit, 104 ...
Decoding circuit, 106 ... processing circuit, 108 ... control circuit, 110 ...
Interface circuit, 112: Huffman decoding unit, 114: inverse quantization unit, 116: IDCT (inverse DCT transform) unit, 118: control unit.

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-3-65886 (JP, A) JP-A-2-248180 (JP, A) JP-A 1-292987 (JP, A) JP-A-63-1988 286078 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) H04N 5/91-5/956 H04N 5/225 H04N 5/907 H04N 9/79-9/898

Claims (5)

(57) [Claims] An imaging system for generating a video signal;
The image signal obtained by the shadow system is transformed by orthogonal transformation or prediction code.
Preprocessing image data by image information compression means
After that, it is quantized by quantization means, and this quantized output is
The variable-length code is encoded by the variable-length encoding means.
Recording that records encoded image signal data in a readable manner
An electronic camera device that is recorded and stored on a medium
Input means for inputting information corresponding to a desired compression ratio, and the output of the variable-length coding means,
Code amount calculation to obtain and output this as calculated code amount information
From the compression ratio correspondence information input by the input means.
Give information on the total amount of code to be stored per image
A statistical processing command is issued to the
Control means for issuing a processing command, and said control means at the start of execution according to said statistical processing command.
Based on the total code amount information,
Prediction of the quantization width is performed, and information of the predicted quantization width is obtained.
Start to be given to the quantization means and to be executed by an encoding process command
Sometimes a previous prediction based on the calculated code amount information input
Fit in the frame of the total code amount for the information of the quantized width
Obtained information on the quantization width corrected as described above,
Quantization width prediction means for providing quantization width information to the quantization means
And information of the quantization width predicted by the quantization width prediction means,
Means for readable recording on a recording medium is provided.
The quantization means receives the information of the quantization width and
The pre-processed image data is quantized by a quantization width.
An electronic camera device, comprising: 2. An imaging system for generating a video signal.
The image signal obtained by the shadow system is converted into image data, and
Image data is divided into blocks in predetermined pixel units, and each block is
Performs orthogonal transform on the lock in order to obtain the coefficients for each frequency component.
After the data is converted, the data is quantized by a quantization means.
The variable length coding means of the output variable length coding, this
Record variable-length coded image signal data in a readable manner.
Electronic camera device that records and saves data on a recording medium
In the apparatus, the quantization means includes a frequency component for each block.
Uses coefficient data and provisional quantization width coefficients for statistical processing
And perform quantization in order from the low frequency component
Sometimes, using the optimal quantization width coefficient,
Quantization is performed, and the variable length coding means
Calculating means for calculating the code amount of the coded output,
Performs statistical processing, and then controls to perform encoding processing.
In the statistical processing, the frequency of each block
The coefficient data for each component is predetermined in order from the low frequency component.
Using the provisional quantization component for each frequency component
Control the quantization means to perform
The coefficient data for each frequency component for each block is
Quantities using the optimal quantization width coefficient for each frequency component in order from the component
Controlling the quantization means to perform the quantization,
From the total code amount generated during the statistical processing obtained from the
Determine the optimal total code amount to contain the image, and
Control means for setting an appropriate target code amount;
Obtained from code amount information from calculation means obtained during statistical processing
Code amount generated per image and code for each block
Code allocation that determines the allocated code amount for each block from the code amount
The means and the variable length encoding means during the encoding process.
The encoded output of each block to be output is
The coding so as not to exceed the allocated code amount in
An electronic camera device comprising a termination unit. 3. An imaging system for generating a video signal.
The image signal obtained by the shadow system is converted into image data, and
Image data is divided into blocks in predetermined pixel units, and each block is
Performs orthogonal transform on the lock in order to obtain the coefficients for each frequency component.
After the data is converted, the data is quantized by a quantization means.
The variable output is variable length encoded by the variable length encoding means.
Record variable-length coded image signal data in a readable manner.
Electronic camera device that records and saves data on a recording medium
In the apparatus, the quantization means includes a frequency component for each block.
The coefficient data is tentatively calculated for each frequency component during statistical processing.
Quantization is performed in order from the low frequency component using the quantization width coefficient
In the encoding process, the optimal quantization width coefficient for each frequency component is
Configuration that performs quantization in order from the low frequency component using
And the code amount of the encoded output from the variable length encoding means.
Calculating means for calculating
Control to perform encoding processing, and to statistical processing.
And the coefficient data for each frequency component for each block
From the low-frequency component in order.
Quantization means to perform quantization using fractional quantization width coefficient
During the encoding process, the frequency component of each block is controlled.
The coefficient data is sorted in order of frequency components from low frequency components.
Quantization to perform quantization using fractional optimal quantization width coefficient
Controlling the means and obtaining from the calculating means
From the total code amount generated during statistical processing, the optimal
A system in which the total code amount is determined and is used as the optimal target code amount.
Control means and optimal target code amount and obtained during statistical processing
The number of sounds per image obtained from the code amount information from the calculation means
Each block is calculated from the total code amount generated and the code amount for each block.
Code allocating means for determining another allocated code amount;
Each block output by the variable length coding means during processing.
The coded output for each block indicates the allocated code amount in the block.
With truncation means for truncating the encoding so as not to exceed
Electronic camera device. 4. An imaging system for generating an image signal.
Block image signal data for one screen obtained by shadow system
And perform orthogonal transformation etc. for each of the divided blocks.
After the pre-processing, the quantization means
The variable output is variable length coded by the variable length coding means.
Variable length coded image signal data is recorded in a reproducible manner
Camera that records and saves data on a recording medium
In the device, input means for inputting information corresponding to a desired compression ratio and output of the variable length coding means, and the total code amount for each screen is calculated.
Code amount calculation to obtain and output this as calculated code amount information
From the compression ratio correspondence information input by the input means.
Give information on the total amount of code to be stored per image
A statistical processing command is issued to the
Control means for issuing a processing command, and said control means at the start of execution according to said statistical processing command.
Based on the total code amount information,
Prediction of the quantization width is performed, and information of the predicted quantization width is obtained.
Start to be given to the quantization means and to be executed by an encoding process command
Last predicted based on sometimes the calculated code quantity information are entered
Fit in the frame of the total code amount for the information of the quantized width
Obtained information on the quantization width corrected as described above,
Quantization width prediction means for providing quantization width information to the quantization means
And the calculated code amount information at the time of execution by the statistical processing command
Based on the information of the total code amount to be stored,
Code amount allocating means for determining an allocated code amount of the code;
At the time of execution according to the decoding process command,
Outgoing code amount information reaches the allocated code amount in the block.
Then, the code for the block of the variable length
Encoding discontinuation means for controlling the encoding to be discontinued, and information of the quantization width predicted by the quantization width prediction means.
Means for readable recording on a recording medium is provided.
The quantization means receives the information of the quantization width and
A configuration for quantizing the preprocessed image data with a quantization width
The variable length encoding means receives the truncation command
Configuration to abort coding for the block currently being processed
An electronic camera device characterized in that: 5. An imaging system for generating a video signal.
A / D conversion is performed on the image signal obtained by the shadow system to generate a luminance signal.
Orthogonal transform or predictive coding by separating into minute and color signal components
Pre-processed by the image information compressing means that performs
And quantizes the quantized output by a variable length coding means.
, And the variable-length coded image signal
Data is recorded and recorded on a recording medium that can be read
An electronic camera device having input means for inputting information corresponding to a desired compression ratio, and information of a quantization width corresponding to various compression ratios in advance.
From the compression ratio corresponding information input by the input means,
The luminance and chrominance signal components corresponding to the
Width setting means for respectively outputting quantization width information to be changed
And information on the quantization width output from the quantization width setting means.
Means for recording information on the recording medium in a readable manner.
In addition, the quantization means is provided from the quantization width setting means.
Upon receiving the output quantization width information, the quantization width
It is a configuration of quantizing the pre-processed image signal data
An electronic camera device characterized by the above-mentioned.