JP3335236B2 - Digital data processing device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION The present invention relates to a method for recording a color still image on a recording medium in accordance with the JPEG algorithm, for example.
The present invention also relates to a digital data processing device provided in a device for reproducing from the recording medium.

[0002]

2. Description of the Related Art Since image data has a large amount of information, direct processing requires an enormous memory capacity and increases the time required for data communication. Therefore, conventionally, image data is processed after being compressed by encoding.

One of such image data compression algorithms is JPEG (Joint Photographic Expert).
Group). This J
The algorithm (JPEG algorithm) recommended by PEG is composed of a plurality of processes such as a baseline process.
This is a basic function capable of encoding an 8-bit-accurate original image using discrete cosine transform (DCT transform) and Huffman coding, and transmitting, receiving, and reproducing image information.

In the baseline process, the pixel data of each block constituting one screen is subjected to DCT conversion,
A T coefficient is obtained, and the DCT coefficient is quantized by a quantization table. That is, the DCT coefficient is quantized by being divided by each of the quantization coefficients constituting the quantization table. This quantized D
The CT coefficients are Huffman-coded and recorded on a recording medium, for example, as compressed image data.

[0005]

When such data compression is performed, a part of the information of the original image is lost, so that the image quality of the reproduced image is inferior to that of the original image. Therefore, if the value of each quantization coefficient in the quantization table is reduced,
Since the value of the quantized DCT coefficient increases, the image quality of the reproduced image is improved, but there is a problem that the amount of compressed data increases. On the other hand, it is possible to evaluate the image quality of the reproduced image, reset the value of the quantization coefficient so as to obtain a sufficient image quality, and perform data compression again. It takes a long time to process data and the work efficiency is not good.

The present invention solves such a problem. In data processing for quantizing input data using a quantization table, the input data can be converted into input data without increasing the amount of data after quantization. It is an object of the present invention to obtain a digital data processing device that can reproduce close data, has a short data processing time, and has high working efficiency.

[0007]

A digital data processing apparatus according to the present invention quantizes a plurality of input data using a first quantization table including a plurality of first quantization coefficients.
Means for encoding and recording on a recording medium; means for inversely quantizing the quantized data by using a quantization coefficient; and means for individual second so that the inversely quantized data approaches the input data. Means for calculating a quantized coefficient by calculation, generating a second quantized table comprising the second quantized coefficient, and means for recording the second quantized table on a recording medium
It is characterized by comprising and.

[0008]

BRIEF DESCRIPTION OF THE DRAWINGS FIG. FIG. 1 is a block diagram showing a still video camera provided with a digital data processing device according to one embodiment of the present invention.

The image signal of the subject S obtained by the image pickup unit 10 is transmitted to an image compression device 20, subjected to data compression processing as described later, and recorded on a recording medium M such as an IC card. In the recording medium M, in addition to the image signal subjected to the data compression, a quantization table used when reproducing the image signal is recorded.

In the image pickup section 10, the light arriving from the subject S is condensed by a condensing lens 11, and a subject image is formed on a light receiving surface of a solid-state image pickup device (CCD) 12. C
A large number of photoelectric conversion elements are arranged on the light receiving surface of the CD 12,
On the upper surface of the photoelectric conversion element, for example, a color filter in which R, G, and B color filter elements are arranged in a predetermined manner is provided, and each photoelectric conversion element corresponds to one pixel data. . The subject image is converted into an electric signal corresponding to a predetermined color by each photoelectric conversion element, and is converted into an A / D signal.
It is input to the converter 13.

The signal digitally converted by the A / D converter 13 is converted into a luminance signal Y and color difference signals Cb and Cr by a signal processing circuit (not shown).
Is input to The image memory 14 is divided into mutually independent memory areas for storing the luminance signal Y and the color difference signals Cb and Cr, respectively, and each memory area has a storage capacity for one screen. The luminance signal Y and the color difference signals Cb and Cr once stored in the image memory 14 are
For data compression processing, first, the DCT of the image compression device 20 is used.
It is input to the processing circuit 21. Although the DCT processing circuit 21 is shown as one processing circuit in FIG. 1, an independent DCT processing circuit is provided for each of the luminance signal Y, the color difference signals Cb, and Cr.

In the image compression apparatus 20, image data such as a luminance signal Y is divided into 8 × 8 blocks for one screen, and processed in block units. As shown in FIG. 2, each pixel block R1 is composed of 8 × 8 pixel data, and this pixel data indicates, for example, a luminance signal Y.

In the DCT processing circuit 21, the pixel data of the original image is two-dimensionally DCT-transformed for each block R1, thereby obtaining 8 × 8 DCT coefficients R for one block.
2 (image processing data) is required. In the DCT coefficient R2 matrix, the DCT coefficient data (26
0) indicates a DC component, and the other DCT coefficient data indicates an AC component. Further, in this matrix, the components on the right side indicate components having a higher spatial frequency in the horizontal direction of the image, and the components on the lower side indicate components having a higher spatial frequency in the vertical direction of the image.

The DCT output from the DCT processing circuit 21
The coefficient R2 is quantized by the quantization processing circuit 22 using a quantization table (Q _Y , Q _Cb , Q _Cr ) R3. The quantization table R3 includes a luminance signal Y and color difference signals Cb and Cb.
Each component of the DCT coefficient R2 is divided by the corresponding quantization coefficient and quantized. That is, the number of components of the DCT coefficient R2 is the same as the number of quantization coefficients.
Each component of the quantized DCT coefficient R4 is rounded off and converted to an integer, and therefore, a part of the image information is lost in the quantized DCT coefficient R4.

The quantized DCT coefficient R4 output from the quantization processing circuit 22 is input to a Huffman coding processing circuit 23 and is subjected to Huffman coding according to a predetermined algorithm. The image signal (Y ′,
Cb ′, Cr ′) are recorded on the recording medium M. Since Huffman coding is conventionally known, its description is omitted.

The quantized DCT coefficient R4 is input to a Huffman coding processing circuit 23, while
And is inversely quantized. That is, the quantized DCT
The coefficient R4 is multiplied by the quantization table (Q _Y , Q _Cb , Q _Cr ) R3 in the inverse quantization processing circuit 24, thereby obtaining an inversely quantized DCT coefficient R5 as shown in FIG.
Each component of the inverse quantized DCT coefficient R5 is a quantized DCT
If the loss of image information has not occurred at the time of generation of the coefficient R4, it becomes exactly the same as the DCT coefficient R2. However, since a part of the image information has actually disappeared as described above,
It does not completely match the T coefficient R2. In this embodiment, as will be described below, the difference between the inversely quantized DCT coefficient R5 and the DCT coefficient R2, that is, the DCT quantization error is minimized to improve the image quality of the reproduced image.

The inversely quantized DCT coefficient R5 and the DCT coefficient R2 output from the DCT processing circuit 21 are input to a quantization error calculator 25, and the difference between these coefficients R5 and R2, that is, the DCT quantization error R6 is calculated. Is done. The optimum quantization coefficient calculation unit 26 calculates the optimum quantization table R7 using the DCT quantization error R6 as described below.

In the i-th block, the matrix of the quantization table R3 is Q _uv , the matrix of the DCT coefficient R2 is S _iuv , the matrix of the quantized DCT coefficient R4 is r _iuv , and the matrix of the inverse quantized DCT coefficient R5 is S '
_iuv . When the square sum E _uv of the DCT quantization error is obtained for one screen, E _uv = Σ (S ′ _iuv −S _iuv ) ² = Σ (r _iuv × Q _uv −S _iuv ) ² (1) Here, Σ indicates the total sum of all blocks constituting one screen.

[0019] (1) equation is differentiated for _{Q uv, dE uv / dQ uv} = 2Σr iuv - a _{(r iuv × Q uv S iuv} ) (2). Here, Q _uv when the sum of squares E _uv takes a minimum value
Is Q ′ _uv , this can be obtained by changing equation (2) to 0 and modifying the equation. That is, Q ′ _uv = round ( _{Σr iuv} · S _iuv / _{Σr iuv} ² ) (3) Here, round means rounding to an integer.

Optimum quantization table R7 according to equation (3)
Are calculated, and the optimum quantization table generation unit 27 generates the optimum quantization table R7 based on the calculation result. This optimal quantization table R7
Are recorded on the recording medium M together with the image signals (Y ′, Cb ′, Cr ′) as quantization tables (Q _Y ′, Q _Cb ′, Q _Cr ′). Note that, as understood from the comparison with the quantization table R3 in FIG. 2, the optimal quantization table R7 differs from the quantization table R3 in data surrounded by a circle.

FIG. 4 shows an example of a DCT coefficient obtained by inverse quantization using the optimal quantization table R7, that is, an optimal inversely quantized DCT coefficient R8. The data circled is different from the inverse quantized DCT coefficient R5. When the difference between the optimum inversely quantized DCT coefficient R8 and the DCT coefficient R2, that is, the optimum DCT quantization error R9 is obtained, as understood from a comparison between FIGS. Has become.

Therefore, at the time of reproduction, the DCT coefficients (optimal inverse quantization DC) are obtained from the image signals (Y ', Cb', Cr ') recorded on the recording medium M using such an optimal quantization table R7.
When the T coefficient R8) is obtained, the DCT coefficient indicates data as close as possible to the input DCT coefficient. When pixel data is calculated by inverse DCT, the DCT coefficient becomes very close to the input pixel data (pixel data of the pixel block R1). Thus, the image quality of the reproduced image is improved.

In this embodiment, the image signal is transmitted to the recording medium M.
Are not changed in the quantization table R3 used for recording in the input data (D
The amount of data obtained by quantizing each component of the CT coefficient R2) is the same as that of the conventional device. Further, since it is not necessary to perform the compression processing of the image data by the Huffman encoding processing circuit 23 or the like again, the processing time of the image data is short, and the working efficiency is high.

In the above embodiment, the present invention is applied to an apparatus for compressing an image signal in accordance with the JPEG algorithm. However, the present invention can be applied to other data compression. That is, the present invention is not limited to the image processing device, but can be applied to, for example, an audio processing device.

[0025]

As described above, according to the present invention, data as close as possible to input data can be reproduced without increasing the amount of data after quantization, and the time required for data processing is short, and work efficiency is reduced. And a digital data processing device having a high

[Brief description of the drawings]

FIG. 1 is a block diagram showing a still video camera including a digital data processing device according to an embodiment of the present invention.

FIG. 2 is a diagram illustrating an example of a pixel block, DCT coefficients, a quantization table, and quantized DCT coefficients.

FIG. 3 is a diagram illustrating examples of an inverse quantization DCT coefficient, a DCT quantization error, and an optimal quantization table.

FIG. 4 is a diagram illustrating an example of an optimal inversely quantized DCT coefficient and an optimal DCT quantization error.

[Explanation of symbols]

 Reference Signs List 10 imaging unit 20 image compression device M recording medium

Claims (4)

(57) [Claims] 1. A method for quantizing a plurality of input data using a first quantization table including a plurality of first quantization coefficients.
Means for encoding and recording on a recording medium; means for inversely quantizing the quantized data using the first quantization coefficient; and means for causing the inversely quantized data to approach the input data. determined by calculation each second quantized coefficients, means for generating a second quantization table of the second quantization coefficient, the second quantization table the
Means for recording on a recording medium . 2. The digital data processing apparatus according to claim 1, wherein said input data is image processing data comprising the same number of elements as quantization coefficients. 3. The method according to claim 1, wherein the image processing data is obtained by performing a two-dimensional discrete cosine transform on pixel data of an original image.
The digital data processing device according to claim 2, wherein the digital data processing device is a CT coefficient. 4. The quantization table generating means calculates the second quantization coefficient so that the sum of squares of an error between the dequantized data and the input data is minimized. The digital data processing device according to claim 1.