JP3192133B2 - Electronic camera device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to relates to an electronic camera equipment.

[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, 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.

[0005] As a representative example, a scheme which is being studied in international standardization of still picture coding will be briefly 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 transformation 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.

[0008] With this basic part 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 (2), one frame of image data (one frame image presented in the international standardization plan is 720 × 575 pixels) into blocks of a predetermined size (for example, blocks A, B, and C composed of 8 × 8 pixels).
..), And two-dimensional DCT (discrete cosine transform) is performed as an orthogonal transform for each of the divided blocks as shown in (b), and the blocks are 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.
On the × 8 matrix, data indicating the value of the DC component DC is located at the origin position (0, 0 position), and data indicating the maximum frequency value of the AC component AC in the horizontal axis direction is located at the 0, 7 position. The maximum AC component A in the vertical axis direction is located at the 7,0 position.
Data indicating the frequency value of C, and data indicating the maximum frequency value of the AC component AC in the oblique direction are further provided at positions 7 and 7.
At the intermediate position, the frequency data in the direction associated with each coordinate position is stored in such a manner that the frequency data having higher frequency than the origin side appears.

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,
Regarding the DC component DC, the difference value between the DC component of the neighboring block and the DC component is expressed 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 coded together. Data (d
1, 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) and the succeeding number. 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. The more the center, the smaller the number of data bits and the closer to the periphery. 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.

With this basic part alone, the code amount is not constant for each image because Huffman coding, which is entropy coding, is used. 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). From the total code amount, 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 using Newton- Predicted by Newton Raphson Iteration (h).

Next, using the quantization width coefficient α (i), the above-described processing after quantization of the basic portion is repeated. And
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 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.

[0020]

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 transformation typified by discrete cosine transformation by dividing 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 that combines the encoding is capable of high-efficiency compression, it uses variable-length coding, so the code amount is not known until the coding is actually finished, and the code amount is controlled. There was a problem that it was difficult.

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, JP-A-63-28607
As disclosed in Japanese Unexamined Patent Publication No. 8 (1994) -208, it is possible to switch between a mode in which data is recorded as it is and a mode in which data is compressed and recorded, and in Japanese Patent Application Laid-Open No. 1-292987, the degree of compression is switched. It has been proposed that a plurality of image quality modes can be selected. 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.

Since the bandwidth of the color signal perceived by humans may be narrower than that of the luminance signal, the luminance signal component and the color signal component of the image are separated to control the quantization width, and the color signal Is reduced as compared with the luminance signal, it is possible to reduce the information amount without deteriorating the image quality of the reproduced image.

However, in the above-described conventional technique, since the quantization width α is controlled without distinguishing the luminance signal and the chrominance signal, there is a problem that the information amount increases.

Further, when the amount of information increases, it takes time to record the information, and this has been a problem particularly in an electronic camera that requires quick shooting. Further, when the amount of information of an image per frame increases, the number of recordable images that can be recorded on a recording medium also decreases. Further, in an apparatus such as an electronic camera having a function of decoding and reproducing and displaying a compressed image signal, there is a problem that the image quality of a reproduced image is deteriorated and that it takes time to reproduce.

[0028]

An object of the present invention is to decode variable-length coded image signal data recorded on a recording medium, and to decode the decoded data with respect to a luminance signal component and a chrominance signal component read from the recording medium. By performing inverse quantization based on the information on the quantization width of, even if the bandwidth of the color signal component is narrower than the bandwidth of the luminance signal component, it is possible to quickly reproduce the image without deteriorating the image quality. An electronic camera playback device is provided.

[0030]

In order to achieve the above object, the present invention is configured as follows. That is, the video signal
And an image signal obtained by this imaging system.
Image information pressure for performing orthogonal transform or predictive coding
After preprocessing the image data by the compression means,
And quantized output by the variable length coding means.
Huffman-encoded image signal
Data is recorded and recorded on a recording medium that can be read
The stored image signal data is decoded by the decoding means.
That is decoded and obtained as a reproduced signal of the image.
A camera playback device, wherein the quantization means includes the preprocessing
With the quantization width given for the processed image data
Quantized image for each component quantized for each degree signal component and color signal component
It has a function to output image data, and has a desired compression ratio.
Input means for inputting the information corresponding to the variable length code catheter
Receives the output of the stage, calculates the total code amount for each screen, and calculates
A code amount calculating means for outputting as the code amount information output, the entering
From the compression ratio correspondence information input by the force
Information on the total amount of code to be stored
Issue a processing instruction, and when the statistical processing is completed, an encoding processing instruction
Control means for issuing an instruction, and execution execution by the statistical processing command.
At the beginning, based on the information of the total code amount from the control means,
The quantization width corresponding to the frame of the total code amount is predicted, and the prediction is performed.
The information of the measured quantization width is given to the quantization means,
The calculation code input at the start of execution according to the processing command
Before the quantization width information predicted previously based on the amount information,
Information on the quantization width corrected to fit within the total code amount
Obtaining the corrected quantization width information to the quantization means.
A quantization width estimating means, and the prediction of the quantization width estimating means
The quantization width information is combined with the quantization width information corresponding to the luminance signal.
The recording medium is divided into quantization width information corresponding to color signal components.
Record readable on the body and the given correction
Brightness quantized by the quantization means in quantization width information
Image data for each of the degree signal component and the color signal
One Huffman encoded image signal data by encoding means
And receive it as input and read it to the recording medium
Recording means for recording the variable-length encoded image signal data recorded on the recording medium, and information on the respective quantization widths corresponding to the luminance signal component and the chrominance signal component related to the variable-length encoded image signal data. Reading means for reading the image signal data, Huffman decoding means for decoding the read image signal data ,
Inverse quantization means for inversely quantizing the data decoded by the Huffman decoding means with the quantization width based on information of each quantization width for the luminance signal component and the chrominance signal component read by the reading means; Output means for performing an inverse orthogonal transform of the dequantized data on a block- by- block basis, converting the data into an image signal and outputting the image signal, and obtaining an output image signal from the output means as a reproduced signal of the image. It is characterized by.

That is, the present invention relates to a reproducing technique for reproducing variable-length coded image signal data which is photographed by an electronic camera device capable of recording a photographed image at a desired compression ratio and recorded on a recording medium. In the recording medium, variable-length coded (Huffman coded) image signal data and information on quantization widths corresponding to luminance signal components and chrominance signal components related to the image signal data are recorded. Therefore, the reading means can read these data by mounting the recording medium. When reading is performed by the reading means, the read variable-length coded image signal data is decoded by the decoding means and supplied to the inverse quantization means. On the other hand, since the information of the quantization width read by the reading means is given to the inverse quantization means, the inverse quantization means outputs the data decoded by the decoding means to the quantization width read by the reading means. Is inversely quantized with the quantization width based on the information of (1). The output means converts the inversely quantized data into an image signal and outputs the image signal. The output image signal from the output means is obtained as an image reproduction signal and displayed on a monitor device to be reproduced as an image, or printed and output by a printer or the like so that the image can be appreciated.

[0032]

In particular, in the present invention, the variable-length coded image signal data recorded on the recording medium is decoded, and the decoded data is used for each of the luminance signal component and the chrominance signal component read from the recording medium. Inverse quantization is performed based on information on the quantization width. As a result, even if the bandwidth of the color signal component is narrower than that of the luminance signal component, quick reproduction is possible without deteriorating the image quality.

[0034]

Embodiments of the present invention will be described below with reference to the drawings.

First, in order to make the present invention easy to understand, a basic concept of the present invention will be described.

That is, according to the present invention, as the first pass processing, statistical processing is performed by quantizing and encoding with the quantization width corrected by the provisional quantization width coefficient calculated corresponding to the target code amount, 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 optimum quantization width and determines the amount of code to be allocated to each block. The prediction of the optimum code amount coarsely (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 process is sufficient. 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 of 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, the code amount of the entire image is calculated as long as it does not exceed 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 determined quantization width and final encoding is performed.

According to the present invention, in the encoding process, the encoding is discontinued 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. The block that has not exceeded ends coding without any problem, that is, outputs EOB. In the block that has been exceeded in the middle, the high-frequency component beyond that is not coded, the coding is discontinued, and the coding of the block is terminated, that is, the EOB is output. At this time, since the EOB is also one of the Huffman codes, it is necessary to include the EOB within the allocated code amount.

In this way, for example, if the coding is completed without cutting off half of the blocks and half of the blocks are omitted with a part of the very high frequency being omitted and the coding is completed, the information missing 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 one 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 the 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 includes an image pickup system 40 for picking up an image, a signal processing circuit 60 for performing predetermined signal processing on the output of the image pickup system 40, a pre-processing unit and a linear quantum An encoding circuit 80 which has an encoding and entropy encoding function, and compresses and outputs the output of the signal processing circuit 60; an image data encoded by the encoding circuit 80; ) On a recording medium 71, a switch 30 for setting and inputting a desired data compression ratio, and a control circuit 90 for controlling the entire system.

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

The image pickup system 40 includes a lens 40a for forming an image of an optical amplifier and an image pickup device 40b such as a CCD. The signal processing circuit 60 includes an amplifier 60a for performing amplification and noise removal, 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 a color signal. Is provided. The encoding circuit 80 includes, for example, an orthogonal transformation unit 4 that performs orthogonal transformation such as DCT (discrete cosine transformation), a quantization unit 6 that performs linear quantization, and a Huffman encoding unit 8 that performs Huffman encoding as entropy encoding. , A quantization width prediction unit 12, a code amount calculation unit 14, a code amount allocation unit 20,
It has a code truncation unit 16 and a control circuit 18 for performing control processing in the encoding circuit 80.

The recording system 70 includes an interface circuit 70
a 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, in which 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. I have.
Reference numeral 49 denotes 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 kinds 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, the information 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 a value of the obtained compression rate and a value of the number of images that can be recorded on the memory card and displayed on the LCD display 48 of the operation unit. . 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. When the shutter operation button 50, which is a trigger switch, is pressed, a shutter function is activated to form a subject image on the image sensor 40b, and a charge image is accumulated in the image sensor 40b in accordance with this image. Therefore, a video signal can be obtained from the image sensor 40b by reading and controlling this.
These controls are also controlled by the control circuit 90.

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

The output video signal of the imaging system 40, which has been digitally converted by the A / D converter 60b, is stored in a buffer memory 60c having a capacity of one frame, for example, and is read out to the process circuit 60d. By being given, it is separated into a Y component which is a luminance signal system and Cr and Cb components which are a chroma (C: color difference signal) system. The image data stored in the buffer memory 60c is
For example, in order to first perform statistical processing on a luminance signal, the processing circuit performs a process processing on the Y signal of the image signal.
The component data is obtained and supplied to an encoding circuit 80 to perform an encoding process on the Y component data. When the process is completed, next, a process process is performed on the chroma Cr and Cb component data. Perform encoding processing.

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, as an example, the block size is 8 ×
8, the 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 provided to a subsequent processing system to perform statistical processing on the Y component data. In order to enter the statistical processing for the data of the chroma Cr and Cb components, the reading and blocking of the data of the chroma Cr and Cb components are started. In the chroma-based blocking, it is assumed that all the image data of the Cr component are first 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 coding circuit 8 scans from a low frequency component to a high frequency component by a technique 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 performing Huffman coding. Regarding the AC component [AC], the conversion coefficients are sequentially checked from the second to the 64th in the scanning order in FIG.
(Zero run) and the value of the effective coefficient perform two-dimensional Huffman encoding and output. Further, when an invalid coefficient continues from a certain coefficient to the 64th coefficient, an EOB (end of block) code indicating the end of the block is output. When the censoring signal is input, the encoding 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, C
The code amount of each block of each r and Cb component and the integration of the code amount are performed, the code amount data of each block of each of Y, Cr and Cb components are collected, and the code amount of the entire image is calculated. For data of the entire code amount, 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 and uses the code amount information to calculate the quantization width using the relationship of equation (1) described later. The initial value of the coefficient α is set and output to the quantization circuit 6, and prior to the start of the second pass, the code amount calculation circuit 1
For example, the Newton-Raphson method (Newton-Raphson iteratio) is used to calculate the code amount of the entire image input from the step 4 and the target code amount which is the maximum allowable data amount per image.
Using n), the quantization width coefficient α that is optimal for approaching the target code amount is predicted in consideration of the quantization width coefficient actually used this time.

The code amount allocating circuit 20 calculates the allocated code amount of each block from the code amount of the image data for each block input from the code amount calculating circuit 14, the code amount of the entire image, and the target code amount. And outputs the result to the encoding termination 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, and converts the code amount information of the corresponding block position in the code amount information table into the code amount information input from the code amount calculating circuit 14. On the other hand, the assigned code amount of each block is calculated from the code amount of each block, the code amount of the entire image, and the target code amount input from the code amount calculation circuit 14, and the 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 given to the coding truncation circuit 16 when the corresponding block is subjected to entropy coding processing.

The encoding termination circuit 16 is provided with a code amount allocating circuit 2
Subtract the code amount of each block from 0 from the allocated code amount,
When the remainder of the allocated code amount becomes smaller than the total code amount of the code amount to be transmitted and the EOB code, a truncation signal is output and given to the entropy coding circuit 8, and the coding of the block is terminated. It has the functions described above.

Therefore, the coding truncation circuit 16 refers to the allocated code amount, and inputs the code amount to be transmitted and E
If the allocated code amount does not exceed even if the OB code is transmitted,
The truncation is not performed, the coding of the block is completed, 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 transfers the connected codes to a recording medium such as a memory card. It functions to write to the recording system 22 configured.

In the present system, statistical processing is first performed by using a predetermined standard quantization width coefficient α determined according to the shooting mode (first pass), and information for each block necessary for optimization is obtained. The amount, the information amount of the entire image, and the like are checked, and then processing for performing optimized coding based on the information obtained by the statistical processing is started (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 Even if it is used, a procedure such as quantization processing, entropy coding of a transform coefficient obtained by this quantization, and output processing for storing all codes of an image to be processed is performed. Thereby subjected, but it is assumed that the entire control management are to perform by the control circuit 18 in FIG. Note that functions such as 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 thereto.
The image data encoded and output by the encoding circuit 80 and the quantization width (or information corresponding thereto) are stored in the recording medium 71 via the interface circuit 70a.
It is configured to be recorded in.

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 the optimum code amount to the encoding circuit 80 as target code amount setting information.

In this way, the number of recordable images is set.

Next, when photographing is performed, a copy body 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. The image signal obtained by the imaging element 40b is input to the signal processing circuit 60, where it is temporarily stored in the buffer memory 60c after being amplified by the amplifier circuit 60a in the signal processing circuit 60 and A / D converted by the A / D converter 60b. You. And after this,
The signal processing circuit 6 is read from the buffer memory 60c.
Processing such as band correction and color signal formation is performed by the process circuit 60d within 0.

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

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

In this embodiment, the signal processing circuit 60 outputs 1
Output is performed on the Y component (luminance component) of the image signal data for the image, and after the subsequent processing (statistical processing) is completed, all the image data of the Cr component is divided into blocks. , A statistical process is performed in the latter stage, and then, a process of dividing the image of the Cb component into blocks and performing the statistical process in the subsequent stage is performed.

The encoding circuit 80 supplies the input data received from the signal processing circuit 60 to the orthogonal transformation circuit 4.

Then, the orthogonal transformation circuit 4 performs block-wise input image data (hereinafter, referred to as block image data).
For each block, for example, a discrete cosine transform (D
CT) to perform a 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 same number of cosine waves as the number of input samples.

The orthogonally transformed block image data (transform coefficients) is 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) 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 transform coefficient is quantized with the quantization width multiplied by the standard (temporary) quantization width coefficient α given by the control circuit 18 (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 lower frequency components to higher frequency components.

Since the first data in the scanning order in FIG. 9 is the DC component DC, the data of the DC component DC is the same as the DC component DC of the immediately preceding entropy-encoded block (the immediately preceding block). The difference value diff-DC is Huffman-coded (FIGS. 8 (d1) and (e1)).

For 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 if a conversion coefficient that is not 0 (ie, a valid coefficient) comes out, it exists immediately before that. Two-dimensional Huffman coding is performed using the number of consecutive 0 (invalid) coefficients (zero run) and the value of the effective coefficient ((d2), (e2)).

Further, the entropy coding 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 calculating circuit 14 calculates the code amount of each block of the Y, Cr, and Cb sentences in order to calculate the code amount of the whole of the input Y, Cr, and Cb components. (G2), and the code amount data for each block is output to the code amount allocation circuit 20. The code amount allocating circuit 20 writes the code amount data of each block as code amount information of the corresponding block position in the code amount information table.

When the Huffman encoding process for all the Y, Cr, and Cb components for all blocks of one image is completed, the code amount calculating circuit 14 controls the code amount of the entire image under the control of the control circuit 18. Is output to the quantization width prediction circuit 12, and the code amount data of the entire image is output to the code amount allocation circuit 20.

The quantization width prediction circuit 12 uses the input code amount data of the entire image and the target code amount data, for example, by using the Newton-Raphson iteration method, to obtain an optimal code amount close to the target code amount. The quantization width coefficient α is predicted based on the actually used quantization width coefficient (see FIG. 8 (h
2)).

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. 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 supplied to the coding truncation circuit 16 when the corresponding block is subjected to entropy coding processing.

Thus, the first pass, that is, the first encoding (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 on the Cr and Cb components. That is, first, the image data is divided into blocks and read, and the Y component (luminance) image signal data extracted and output from the signal processing circuit 60 is input to the encoding circuit 80 (a). The input block image data is input to the orthogonal transformation circuit 4 in the encoding circuit 80, and the orthogonal transformation is performed again (b). The transform coefficient obtained by this 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 determined by the quantization width prediction circuit 12 in the previous pass.
Is the calculated optimal quantization width coefficient α.

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, of the conversion counts of the block image data, first, the difference value diff-DC of the DC component DC is Huffman-coded ((d1), (e1)).
1)) Then, the AC component AC is sequentially extracted by zigzag scanning to perform two-dimensional Huffman coding ((d
2), (e2)).

However, every time a Huffman code for one element (one position in the matrix) is generated, the code amount allocating 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 the EOB is transmitted based on the allocated code amount of each block. If it does not exceed, no truncation signal is generated,
A process of subtracting the code amount to be transmitted from the allocated code amount of the block is performed. 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 cutoff circuit 16 sends the cutoff 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.

Accordingly, 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 EOB code to the code output circuit 10. If the truncation signal is input before Huffman coding for all elements of the matrix is not completed, the entropy coding circuit 8 replaces the code with EO.
The code B is output to the code output circuit 10.

The code output circuit 10 temporarily stores the coded data.

Then, the entropy coding circuit 8 shifts to the Huffman coding of the next block obtained from the quantization circuit 6.

By repeating such an operation, the processing of all the blocks of the image of one screen is completed, and the entire encoding processing is completed. 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 on 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 the data by connecting the variable-length Huffman codes from the entropy coding circuit 8 to the memory card as the storage medium 71.

The writing to the storage medium 71 by the output of the code output circuit 10 may be performed at the end of the second pass, but may be performed at the end of the second pass.
The result of joining variable-length Huffman codes at the stage of entering the path may be written to a storage medium sequentially in units of one byte or several bytes as soon as they are collected.

Prior to this, the code output circuit 10 writes the optimum quantization width coefficient α used for coding into 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 (target code amount) per recorded image 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. Further, the processing may be performed before the A / D conversion, and may be 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.

In the present invention having the configurations shown in FIGS. 1 and 2 described above, the quantization width close to the optimum quantization width set from the target code amount is used 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.

[0110] Thus, the screen data obtained by the imaging system by shooting can be accurately encoded in a short time to fill the frame of the target code amount, thereby bringing the code amount close to the allowable code amount. 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 briefly described.

When image data is preprocessed, its output is quantized, and this quantized output is subjected to variable-length encoding, the amount of code generated can be changed by changing the quantization width of this quantization. This is a well-known fact. This is because variable-length coding represented by Huffman coding reduces the amount of code necessary to represent data using the bias in the probability of occurrence of the data to be coded. ,
Since "changing the quantization width" also 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.

Incidentally, 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, the relative ratio to a certain quantization width is SF
If the generated code amount is represented by the number of bits (bit rate) per pixel (BR) and this is BR, the following relationship is obtained: log BR = a × log SF + b (1) 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 typical b is obtained from the occurrence frequency distribution.

Although the above has been described with reference to an example, 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.
In the compression coding, a series of processes is performed in the first pass with a provisional quantization width calculated based on the target code amount, and as a result, an optimum quantization width is obtained based on the obtained result. The second pass is performed to complete the process by two processes of obtaining the final compressed and encoded data, and the optimum α is found by the first pass. In FIG. 3, in order to make the flow of processing of the encoding circuit 80 easy to understand, the signal flow in the first pass is indicated by a dotted arrow P1.
Further, 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. The user sets the desired number of recordable images by operating the switch 30, and the control circuit 90 selects the optimum code amount according to the set number of recordable images. Encoding circuit 80
Is realized by giving Note that in the initial state, the standard number of recordable images is set in advance.

When the photographing is performed, the photographing system 40
An image signal is output from the image sensor in the inside. The output image signal is converted into a digital signal in the signal processing circuit 60 and stored in the buffer memory.
The data is read out in pixel block units, and is separated into a Y component, then a Cr component, and then a Cb component. This separation is first performed for the Y component, and the Y component image data output in units of 8 × 8 pixels is input to the orthogonal transform circuit 4 and orthogonally transformed for each block (in this example, DCT: discrete cosine Transform (Discrete Cosine Transform): predictive coding (DPCM) may be used). The DCT transform coefficient obtained by the orthogonal transform circuit 4 is
On the other hand, the target code amount is output from the control circuit 18 to the quantization width prediction circuit 12, and the quantization width prediction circuit 12 calculates the quantization width from the target code amount using the relationship of the equation (1). The initial value of the coefficient α is set and output 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, the conversion coefficients are examined in order from the second to the 64th in the scanning order, and the conversion coefficient becomes 0.
If a non-valid (ie, valid) coefficient comes out, two-dimensional Huffman coding is performed by the number of consecutive 0 (zero; invalid) coefficients that existed immediately before (zero run) and the value of the valid coefficient. Will be If the invalid output continues to the 64th coefficient after a certain coefficient, an EOF (end of file) code indicating the end of the block is output. The variable-length encoding circuit 8 outputs the code amount generated in each block to the code amount calculation circuit 14 each time the above-described encoding is completed in each block.

When such a process for the Y component is completed, a similar process is performed for the Cr component and the Cb component.

When the coding of one image is completed, the code amount calculating 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.
The total code amount value is output to the quantization width prediction circuit 12, and is output to the code amount allocation circuit 20 for each block and the entire image.

When the first pass encoding process is completed, a second pass encoding process is 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 separated into a Y component, then a Cr component, and then a Cb component, and the image data of each component is 8 × 8 pixels. After processing such as blocking is input to the orthogonal transform circuit 4, the orthogonal transform (DCT transform) is performed for each block, whereby the DCT transform coefficients obtained by the orthogonal transform circuit 4 are transmitted to the quantization circuit 6. Is entered.

On the other hand, the quantization width prediction circuit 12 obtains a more suitable quantization width coefficient α from the total image code amount obtained by the encoding in the first pass and the target code amount given from the control circuit 18. And outputs the result 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 coding is obtained at the time of the first pass coding, 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 output to the recording system 70 via the code output circuit 10 and recorded.

Next, the recording medium 7 recorded by the recording system 70
The reproduction of the first compression-encoded recording image data will be described.

FIG. 4 shows the structure of the reproducing apparatus. In the figure,
Reference numeral 100 denotes a playback device main body. The playback device main body 100 includes a reading unit 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 encoded data, and 114 denotes data obtained by Huffman decoding, which is read out from the storage medium 71 based on the quantization width information set and input. An inverse quantization unit for quantizing 116, an IDCT (inverse DCT transform) unit for inverse DCT transforming the data obtained by the inverse quantization and outputting it as video signal data, and 118 a control for controlling these Department.

The processing circuit 106 includes a buffer memory 120,
An encoder 122 and a D / A converter 124 are provided.
The buffer memory 120 is a memory that temporarily holds the video signal data output from the decoding circuit 104, and the encoder 122 converts the video signal data read from the buffer memory 120 into an NTSC video signal. The / A converter 124 converts the NTSC video signal into an analog signal and outputs 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 data, control for controlling the reading unit 102 is performed. Although not shown, the playback device main body 100 has a frame feed switch and 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.
The recording medium (memory card) 71 on which the compression-encoded video signal data is recorded is the reading unit 10 of the main unit 100 of the reproducing apparatus.
2, the control circuit 108 first reads the reading unit 10
2 is controlled so as to read out information on the quantization width at the time of encoding. As a result, in the reading unit 102, the recording medium 71
The information of the quantization width at the time of encoding is read out from, and this information is set in the inverse quantization unit 114 of the decoding circuit 104.
Subsequently, the control circuit 108 controls the reading unit 102 to read the video signal from the recording medium 71.
Reads the video signal sequentially from the recording medium 71 and inputs the video signal to the decoding circuit 104. In the decoding circuit 104 receiving this, the Huffman decoding unit 112 decodes the Huffman code to obtain a quantized coefficient. The quantized coefficients obtained in this way are supplied to the inverse quantization circuit 114 for inverse quantization. Here, the inverse quantization is performed by using the information of the quantization width set previously.

The transform coefficient obtained by the inverse quantization has the ID
The inverse DCT is performed for each block in the CT unit 116,
The original video signal is restored. In this way, Y, Cr,
The video signal is restored in the order of Cb, output from the decoding circuit 14, 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 TV signal scanning order, and
2, the video signal is converted into an NTSC video signal. The signal is further 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, and a hard copy can be obtained by giving it to a printing device such as a video printer and printing it. It can be viewed in the same way as.

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 with one common hardware without providing a hardware wafer for each compression ratio.

In the embodiment, the encoding process is performed in the first pass and the second pass.
Although the two-pass method is adopted in which the processing is completed in two passes, the present invention is not limited to this, and a method in which encoding is performed in one pass using a quantization width set from the compression ratio is sufficiently compressed for practical use. Rate control. In addition, although an example using a memory card as a recording medium has been described, a floppy disk, an optical disk, a magnetic tape, or 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. The value of the quantization width itself is recorded on the recording medium.
The quantization width value may be converted or encoded and recorded. The preprocessing encoding may be KL conversion, DPCM conversion, or the like. The entropy coding may be arithmetic coding, run-length coding, or the like.

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 is obtained from the beginning, approximately one bus 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; 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 a temporary quantization width, and an 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 sequentially performed on each block to obtain coefficients for each frequency component.
The T coefficient data is quantized in order from the low frequency component using the provisional quantization component coefficient α for each frequency component, and this is Huffman-coded, and then the total code amount generated by this and the code amount for each block From this, the optimal target code amount is determined, and the target code amount is distributed by the generated code amount for each block to determine the allocated code amount for each block. Further, for each frequency from the total code amount generated and the target code amount, Determine the optimal quantization width of
The image obtained by the photographing is divided into blocks, and then DCT is sequentially performed on each block to obtain coefficients for each frequency component, and the DCT coefficient data for each frequency component is sequentially determined from the low frequency component for each of the determined frequency components. Performs quantization using the optimal quantization width coefficient α, performs Huffman encoding, and records the code generated by the Huffman encoding within the range not exceeding the allocated code amount in the block. Exceeding stops the encoding.

The control circuit 90 has a control function for performing such processing. Then, first, the control circuit 90
The control circuit 90 determines the most suitable target code amount for the image under processing 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 is set in the control circuit 18 and the control circuit 18
Then, the quantization width prediction circuit 12 is controlled to predict the optimum quantization width coefficient α for each frequency component from the determined target code amount and the total code amount at the time of the statistical processing. The optimum quantization width for each frequency component obtained by correcting with the optimum quantization width coefficient α for each frequency component is given from the quantization width prediction circuit 12 to the quantization circuit 6.
Then, the quantization of the image data (DCT transform value) for each block is performed with the optimal quantization width for each frequency component.

The quantized output is supplied to an entropy coding circuit 8, and the generated code is subjected to coding 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 read out in units of 8 × 8 pixel blocks. The image data of the digital signal read in block units is encoded by an encoding circuit 8.
Input to 0. The image data input to the encoding circuit 80 is processed by the orthogonal transformation circuit 4 in the encoding circuit 80.
First, DCT is performed for each block to obtain a DCT coefficient which is a value for each frequency component. And this obtained D
For the CT coefficient, the quantization circuit 6 in the encoding circuit 80
As a result, linear quantization is performed using a provisional quantizer width preset for each frequency component for each frequency component.

The quantized transform coefficients are supplied to the encoding circuit 80
Are subjected to Huffman encoding by the entropy encoding circuit 8.

On the other hand, the code amount calculating 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. . Code amount allocating circuit 2 in coding circuit 80
0 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 the target code amount most suitable for the image being processed from the value of the total code amount.
Set to.

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 because the image data is read out again from the buffer memory 60c, processed into blocks, and
Start by typing in. The encoding circuit 80 supplies the input image data to the orthogonal transformation circuit 4, performs DCT by the orthogonal transformation circuit 4, and supplies the obtained DCT coefficients to the quantization circuit 6.

On the other hand, in the quantization width prediction circuit 12 of the encoding circuit 80, a more suitable quantization for each frequency component is obtained from the total image code amount and the target code amount obtained by the encoding in the first pass. The quantization width coefficient α is predicted, and the predicted value is output to the quantization circuit 6. The code amount allocating circuit 20 determines the allocated code amount for each block by proportional distribution or the like from the stored code amount for each block and the target total code amount from the control circuit 90, and stores this. .

In the quantization circuit 6, 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 is used. 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). Quantity allocation circuit 20
Is compared with the assigned code amount of each block stored in the above. If it exceeds this, the code truncation circuit 16 instructs the entropy coding circuit 8 to terminate the coding. 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 stop 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 coded 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.

Note that, in this method, Y as in the previous embodiment is used.
(Luminance) component), C (chroma) component (C component is
(It is also possible to subdivide the color components into r and Cb). 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.

[0163]

As described in detail above, according to the present invention,
The variable-length coded image signal data recorded on the recording medium is decoded, and the decoded data is decoded based on the information of each quantization width for the luminance signal component and the chrominance signal component read from the recording medium. By inverse quantization, even if the bandwidth of the color signal component is narrower than that of the luminance signal component, rapid reproduction can be performed without deteriorating the image quality.

[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 discontinuation circuit,
18, 18a: control circuit, 20: code amount allocating circuit, 24
... DCPM circuit, 30 ... switch, 40 ... imaging system, 48
... LCD display, 60 ... signal processing circuit, 80 ... encoding circuit, 70 ... recording system, 71

──────────────────────────────────────────────────続 き Continuation of the front page (56) References JP-A-63-76684 (JP, A) JP-A-63-286078 (JP, A) JP-A 1-292987 (JP, A) JP-A-3-29 65886 (JP, A) (58) Field surveyed (Int. Cl. ⁷ , DB name) H04N 5/76-5/956 H04N 5/225-5/243 H04N 9/79-9/898 H04N 101: 00

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 Huffman coding is performed by the variable length coding means.
Record the encoded image signal data in a readable manner
Record and save on a recording medium, and save the saved image signal data.
Data is decoded by a decoding means to obtain a reproduced signal of the image.
An electronic camera device according to claim 1, wherein said quantizing means comprises:
Luminance signal component and chrominance signal component with given quantization width
Function to output quantized image data for each component
To have, also, an input unit configured to input information corresponding to a desired compression ratio, receives the output of the variable length coding means, the total code amount of each screen
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
Obtain the information of the corrected quantization width and obtain the corrected quantization width
A quantization width prediction unit for providing information to the quantization unit; and information on the quantization width predicted by the quantization width prediction unit.
Quantization width information corresponding to the degree signal and color signal components
Divided into quantization width information and recorded readable on the recording medium
And at the given corrected quantization width information
The luminance signal component and the chrominance signal component quantized by the quantization means
The separated image data is further processed by the variable-length coding means
This is used as input for image signal data
Recording means for readably recorded before type recording medium receives
When the luminance signal component and a reading means reading information for each of the quantization width corresponding to the color signal component associated with the variable length coded image signal data recorded on the recording medium to the variable-length coded image signal data Huffman decoding for decoding the read image signal data
No. means and, contrary to inverse quantization in the quantization width based on the luminance signal component and information of each of the quantization width for the chrominance signal components read by said reading means data decoded by the Huffman decoding means A quantizing means, and an inverse orthogonal transform of the dequantized data for each block.
Output means for converting to an image signal and outputting the image signal,
Electronic camera equipment, characterized in that the output image signal from the output means to obtain a reproduced signal of the image. 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 data conversion, a predetermined quantization width is set by the quantization means.
And quantized, and the quantized output is sent to the variable-length encoding means.
Huffman coded image signal
Signal and quantization information corresponding to the quantization width
Quantization width information corresponding to the color signal and quantization width corresponding to the color signal
Recorded on a recording medium that can be read out separately from information
And save the stored image signal data as a decryption method.
So that the decoded signal is obtained as a reproduced signal of the image.
An electronic camera device, wherein the quantizing 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,
A configuration to perform quantization, also calculates the code amount of the coded output from the variable length coding means
Calculation means, to perform statistical processing first, and then to perform encoding processing
Control, and in the statistical processing,
The coefficient data for each frequency component is sequentially calculated from a low frequency component.
Using a predetermined provisional quantization component for each frequency component
Control the quantization means to perform quantization, and
Represents the coefficient data for each frequency component of each block,
Use the optimal quantization width coefficient for each frequency component in order from the frequency component
Control the quantization means to perform quantization,
Total code amount generated during the statistical processing obtained from the calculating means
Determine the optimal total code amount to fit the image from
A control unit for setting the optimal target code amount; and an optimal target code amount and the calculation means obtained at the time of statistical processing.
Generated per image obtained from code amount information from the stage
From the total code amount and the code amount for each block,
Code allocation means for determining the code amount, and before output from the variable-length coding means during the coding process
The encoded output of each block is
Censoring to stop encoding so as not to exceed this code amount
And a variable length coded image signal data recorded on the recording medium.
And the luminance signal associated with the variable-length coded image signal data.
The information of each quantization width corresponding to the signal component and the color signal component
Reading means for reading, and reading the read variable-length coded image signal data.
Huffman decoding means for decoding the Huffman code, and reading the data decoded by the Huffman decoding means.
To the luminance and chrominance signal components read by the
Based on the information of each quantization width,
Inverse quantization means for inverse quantization, and inverse orthogonal transform of the inversely quantized data for each block
Output means for converting to an image signal and outputting the image signal,
The output image signal from this output means is used as an image reproduction signal.
An electronic camera device characterized by being obtained by: 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 data conversion, a predetermined quantization width is set by the quantization means.
And quantized, and the quantized output is sent to the variable-length encoding means.
Huffman coded image signal
Signal data and quantization information corresponding to the quantization width
Quantization width information corresponding to the color signal and quantization width corresponding to the color signal
Information on a recording medium that records it in a readable manner.
Record and save and decode this saved image signal data
By means of decoding to obtain a reproduced signal of the image
An electronic camera device according to claim 1, wherein said quantizing 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.
Calculation means for calculating the first, statistical processing is performed first, and then encoding processing is performed.
Control, and in the statistical processing,
The coefficient data for each frequency component is sequentially calculated from a low frequency component.
Using a predetermined provisional quantization component for each frequency component
Control the quantization means to perform quantization, and
Represents the coefficient data for each frequency component of each block,
Use the optimal quantization width coefficient for each frequency component in order from the frequency component
Control the quantization means to perform quantization,
Total code amount generated during the statistical processing obtained from the calculating means
Determine the optimal total code amount to fit the image from
Control means for setting the optimum target code amount, and calculation means for obtaining the optimum target code amount and statistical processing.
Total number of generated symbols per image obtained from these code amount information
Assigned code for each block from code amount and code amount for each block
Code assigning means for determining a signal amount, and before output from the variable-length encoding means during the encoding process.
The encoded output of each block is
Censoring to stop encoding so as not to exceed this code amount
And Huffman-coded image signal data recorded on the recording medium
And a luminance signal related to this Huffman encoded image data
Read the quantization width information corresponding to the
Reading means for reading out, and a Huffman decoding means for decoding the read image data.
And reading the data decoded by the Huffman decoding means.
To the luminance and chrominance signal components read by the
Based on the information of each quantization width
Inverse quantization means for inversely quantizing the data, and inverse orthogonal transform of the inversely quantized data for each block.
Output means for converting the image signal into an image signal and outputting the image signal.
Output image signal from the output means of
An electronic camera device characterized by being obtained. 4. An imaging system for generating an image signal.
Block image signal data for one screen obtained by shadow system
And orthogonal transform etc. is performed for each of the divided blocks.
After performing the preprocessing, the quantization means sets a predetermined quantization width.
And quantize it, and use this quantized output
Huffman-encoded image
The image signal data and the quantization information corresponding to the quantization width are illuminated.
Quantization width information corresponding to the degree signal and the quantum corresponding to the color signal.
Recording medium that can be read and recorded separately from
And save the image signal data.
Decoding means to obtain an image reproduction signal.
A Unishi other electronic camera apparatus, comprising: input means for inputting information corresponding to the desired compression ratio, receives the output of the variable length coding means, the total code amount of each screen
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 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 a block, and when executing by the encoding processing command,
The calculated code amount information is the allocated code in the block.
When the amount reaches the value, the corresponding block of the variable length
Coding abort means for controlling to abort the coding to be performed, 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
Has, recorded on the recording medium Huffman encoded image signal data
And the luminance signal associated with this Huffman encoded image data.
The information of each quantization width corresponding to the signal component and the color signal component
Reading means for reading, and a Huffman decoding means for decoding the read image data
And reading the data decoded by the Huffman decoding means.
To the luminance and chrominance signal components read by the
Based on the information of each quantization width,
Inverse quantization means for inverse quantization, and inverse orthogonal transform of this inversely quantized data for each block
Output means for converting to an image signal and outputting the image signal,
The output image signal from the output means is obtained as an image reproduction signal.
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, and the luminance signal is converted.
Orthogonal transform that separates signal components and color signal components and performs orthogonal transform
After pre-processing by means, it is quantized by quantization means,
This quantized output is converted to a Huffman code by Huffman encoding means.
The Huffman coded image signal data is read.
Record and save on a recordable recording medium
An electronic camera device according to claim 1, wherein said orthogonally transformed image data is quantized.
And information on the quantization width for the luminance signal component and the chrominance signal component
And a quantization width setting means for respectively outputting
Means for outputting the information on the quantization width output from the recording medium
Means for recording in a readable manner, and the quantization means is output from the quantization width setting means.
Received the quantization width information and pre-processed with the quantization width
It has a configuration for quantizing image signal data and records it on a recording medium.
Huffman coded image signal data recorded and this image signal
Corresponding to luminance and chrominance signal components related to data
Reading means for reading information of each quantization width;
Huffman decoding means for decoding the output image data,
Reading the data decoded by the Huffman decoding means
The luminance signal component and the chrominance signal component read by the
Based on the information of each quantization width
Inverse quantization means for quantizing, and the inversely quantized data
Is subjected to inverse DCT for each block, converted to an image signal, and output.
And an output means for force, and the output image signal from the output means, the reproduction signal of the image
An electronic camera device characterized by being obtained by: