JPH06311499A - Picture signal decoding device - Google Patents

Abstract

PURPOSE:To eliminate distortion at high speed through a simple circuit without causing a blur, etc., in a picture. CONSTITUTION:A picture signal decoding device to decode picture data compressed by orthogonal transformation, quantization and variable length encoding at every block is provided with a distortion elimination processing circuit 16 to eliminate the distortion from the picture data obtained by decoding, an orthogonal transformation coefficient obtained by the orthogonal transformation and a judging means 18 to change the distortion elimination characteristic of the distortion elimination processing circuit 16 at every block on the basis of at least one of an orthogonal transformation coefficient obtained by the orthogonal transformation, a motion vector at every block, and block type information.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image signal decoding apparatus, and more particularly to an image signal decoding apparatus which decodes an image transmitted or recorded after being highly compression coded.

[0002]

2. Description of the Related Art When a moving image signal picked up by a solid-state image pickup device such as a CCD is recorded as digital data in a storage device such as a magnetic disk or a magnetic tape, the amount of data becomes enormous. . Therefore, in order to record in a limited storage capacity range, it is necessary to compress the obtained image signal data with some high efficiency.

As a moving image compression method, a method of achieving high compression by utilizing inter-frame correlation as proposed by ISO is generally used. This method will be briefly described with reference to FIG.

FIG. 5 is a block diagram showing a conventional moving image compression method utilizing inter-frame correlation. In the figure, the prediction error signal from which the motion compensation interframe prediction image is subtracted by the difference circuit 1 is DCT (discrete cosine transform).
The circuit 2 performs DCT for each block, and then the quantization circuit 3 quantizes. Further, the quantization result is the coding circuit 4
A variable length code is assigned and recorded at. Further, the quantization result is decoded by the inverse quantization circuit 5 and the inverse DCT circuit 6, and is added by the addition circuit 7 to the motion compensation interframe prediction image. Then, a motion compensation prediction circuit 8 incorporating an image memory having a variable delay function for motion compensation
Then, the motion vector is calculated in order to create the motion-compensated inter-frame predicted image of the next frame.

All the frames are compressed by repeating this series of processing, but the difference is not always coded.
The input image itself may be encoded, which is called an I picture. In addition, the prediction error image has the following 2
There are different types.

[0006] One of them is called a P picture, and it is located in time ahead of the image to be encoded,
This is the difference from the already coded I-picture or P-picture image. In practice, a so-called intra-coding which has a high efficiency of coding the difference from the motion-compensated predicted image or coding without taking the difference is selected.

The other is called a B picture, and is the most significant of the three types of difference coding and intra coding of temporally forward, backward, or interpolated images created from forward and backward. Select the most efficient one. This prediction method can be switched in block units, and selection information is added to the code as a block type.

Further, DCT and variable length codes are used for the signal after motion compensation, the difference between images is obtained, and the redundancy in the time axis direction is reduced, in order to reduce the redundancy in the spatial direction. There is. An encoding method using orthogonal transform such as DCT is also widely used for still image compression, and this method will be described below with reference to FIG.

FIG. 6 illustrates the operation of compressing a still image by a coding method using DCT. First, when a signal f whose redundancy in the time axis direction has already been reduced is input (101). , The input image data f is divided into blocks of a predetermined size to obtain f _b (102), and two-dimensional DCT is performed as orthogonal transformation for each divided block to obtain F _b.
(103). Next, linear quantization is performed according to each frequency component (104), and the quantized value F
Huffman coding is performed on _{Q as} variable-length coding (105). The result is transmitted or recorded as the compressed data C. At this time, the quantization width of the linear quantization is provided with a quantization matrix that represents the relative quantization characteristics in consideration of the visual characteristics for each frequency component,
The quantization width is determined by multiplying this quantization matrix by a constant.

On the other hand, when the image data is reproduced from the compressed data, the quantized value FQ of the transform coefficient is obtained by decoding the variable length code (C) (106).
However, it is impossible to obtain the true value F before quantization from this value, and the result obtained by the inverse quantization becomes F ′ including an error (107). Therefore, IDCT (Inverse Discrete Cosine Transform) is performed on this value (F ') (108), and the resulting value fb' is inversely blocked (109), and the resulting image data f'has an error. It will be included.

Therefore, the image quality of the (110) reproduced image f'reproduced and outputted by the image reproducing apparatus is deteriorated. That is, the error in the value (F ') obtained as a result of the inverse quantization causes deterioration of the image quality of the reproduced image (f') as a so-called quantization error.

More specifically, first, the input image data is divided into blocks of a predetermined size (for example, blocks of 8 × 8 pixels), and each divided block is two-dimensionally orthogonally transformed. DCT of 8x
Sequentially stored in 8 matrices.

When viewed in a two-dimensional plane, the image data has a spatial frequency which is frequency information based on the distribution of grayscale information. Therefore, by performing the above DCT, the image data has a direct current component (DC) and an alternating current component (A).
C), and data indicating the value of the direct current component (DC) is stored at the origin position (0,0 position) on the 8 × 8 matrix. Then, data indicating the maximum frequency value of the AC component (AC) in the horizontal axis direction is at the 0,7 position, and data indicating the maximum frequency value of the AC component (AC) in the vertical axis direction is at the 7,0 position. Furthermore, the AC component (A
The data indicating the maximum frequency value of C) are stored respectively. Further, 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 a higher frequency sequentially appears from the origin side.

Next, the stored data at each coordinate position in this matrix is divided by the quantization width for each frequency component to perform linear quantization according to each frequency component, and this quantization is performed. Huffman coding is performed as variable-length coding on the value. At this time, with respect to the DC component (DC), the difference value from the DC component of the neighboring block is Huffman-encoded. Regarding the AC component (AC), a scan from a low frequency component called a zigzag scan to a high frequency component is performed, and a continuous number (zero run number) of invalid (value “0”) components, 2 of the effective component value that follows
Dimensional Huffman coding is performed to obtain data.

[0015]

In this method, the compression rate is generally controlled by changing the quantization width of the above quantization, and the higher the compression rate, the more
The quantization width becomes large. Therefore, the quantization error becomes large, and the deterioration of the image quality of the reproduced image becomes noticeable.

The quantization error of the transform coefficient tends to appear as so-called block distortion, in which discontinuity occurs at a block boundary portion in a reproduced image, or as mosquito noise in which a haze-like object appears in a flat portion near an edge. is there. Since these distortions are visually conspicuous, even if the S / N is good, the subjective impression is deteriorated.

Therefore, a method of applying a low-pass filter (low-pass filter) to the image reproduced by the decoder as distortion removal processing has been devised. This filter can remove distortion relatively well, but if the image contains edges, etc., they will be blurred, and conversely, the degree of low frequencies that pass will be reduced to reduce blur. If it is made loose, there is a problem that the block distortion cannot be completely removed.

In order to solve this problem, the presence or absence of an edge in an image or distortion is detected, and whether or not to apply a filter is switched according to the result, and a filter is applied only to a portion where distortion exists. There is also.

However, in the distortion removing method as shown in the conventional example, there is still a drawback that the image is blurred, and since the block distortion amount and the like need to be calculated, a long processing time is required and therefore the circuit is The size and power consumption of the device had become very large. Therefore, it is difficult to apply the above-described method to products that place importance on downsizing and high speed, particularly those that handle moving images.

The image signal decoding apparatus of the present invention has been made in view of such a problem, and an object of the apparatus is to realize a high-speed operation without causing blurring in an image with a simple circuit. An object is to provide an image signal decoding device capable of removing distortion.

[0021]

In order to achieve the above object, the present invention provides an image for decoding image data compressed by orthogonal transform, quantization and variable length coding for each block. In a signal decoding device, distortion removal processing means for removing distortion from image data obtained by the above decoding, orthogonal transformation coefficient obtained by the orthogonal transformation, motion vector for each block, and block type And a determination unit that changes the distortion removal characteristic of the distortion removal processing unit for each block based on at least one of the information.

[0022]

1 shows a sigma filter for removing mosquito noise as a distortion removing process according to a first embodiment of the present invention. Target pixel that is attempting to currently handle the x in the figure, when the pixels surrounding the target pixel a ₁ ~a _24, the new x value x 'is expressed by the following equation.

[0023]

[Equation 1]

Here, θ is a threshold value, which is a parameter for changing the noise removal characteristic. In general, as the value of θ is increased, the effect of removing mosquito noise is improved, and a grainy signal in an image is removed. On the contrary, when θ is decreased, the effect of this filter also decreases, and when θ = 0, it is equivalent to not applying the filter at all.

In this embodiment, the values of b _{1 to} b ₂₄ are 1 /
Although the value is set to 24, an appropriate value is selected in accordance with the distortion removal characteristic, and it is desirable to experimentally set the value to satisfy Σb _K = 1. Further, it is desirable that θ be about 1/10 of the maximum pixel value. For example, in the case of an image of 8-bit data, if the value of θ is set to about 20 to 30, distortion can be removed well.

Next, an example of adaptively applying the sigma filter will be described. As described above, this filter can change its characteristic by changing the value of θ. That is, it is possible to reduce the mosquito noise by determining the observability of the mosquito noise from the motion information as described above and changing the characteristics of the filter based on the result.

Further, a method of obtaining the conspicuousness of mosquito noise for each block in an image and using it to change the value of θ will be described below. First, in FIG. 3, which will be described later, the determination circuit 18 determines the DCT coefficient for each block.
To obtain the sum of absolute values of each AC coefficient.
Then, since the complexity of the pattern in the block can be estimated from the resulting power in the spatial frequency plane, filtering with a large value of θ is performed for the block with high complexity.

Further, in this method, when the sum of the absolute values of the DCT coefficients is obtained, the coefficients of all the AC components are not used, but only the coefficients that strongly affect the complexity of the picture are used. Not only can the calculation time be shortened, but also the noticeability of mosquito noise can be accurately determined.

FIG. 2 shows the arrangement of DCT coefficients in an 8 × 8 block, with the DC component in the upper left corner. In this embodiment, the absolute value sum of the DCT coefficients of the hatched portion in the figure is calculated, and θ is increased when this value is large, and θ is decreased when this value is small. By doing so, the mosquito noise removal filter can be adaptively applied to not only the moving image but also the still image.

The second embodiment of the present invention for performing the distortion removing process will be described below with reference to FIG. In the figure, 11 is a variable length code decoding circuit, which decodes code data for each block of an image,
The signal is returned to the inter-frame difference signal via the CT circuit 13, is subjected to distortion removal in the distortion removal processing circuit 16, and is then output to the addition circuit 14. The output of the addition circuit 14 is added to itself via the motion compensation prediction circuit 15 and is supplied to the image output unit 17 as a reproduced image.

That is, in the present embodiment, the distortion removal processing is performed before motion compensation of a signal using inter-frame correlation, that is, on an image obtained by decoding a signal recorded as a DCT coefficient. It is a feature.

For example, the signal of the (n + 1) th frame obtained by taking the differential signal from the nth frame is the signal recorded in a compressed state is also the signal of the interframe difference, and even if this is decoded, the original Will not be an image of. However, the decoded signal of the inter-frame difference signal also shows distortion due to compression, and adding this to the reproduced signal of the nth frame causes the distortion to be accumulated.

Therefore, the configuration is such that distortion is removed at the stage of obtaining the differential signal between frames, and then the previous frame is added. With such a configuration, since the DCT coefficient for the inter-frame difference signal is used for determining the distortion removal characteristic, the distortion can be removed most efficiently. In this configuration, the distortion removal processing is not applied to the so-called reproduced image added to the motion-compensated previous frame signal, but to the inter-frame difference signal, and then the signal is added to the previous frame signal. I am trying to do it.

However, since the image after the distortion removal processing is added for each frame, when the frame using the inter-frame difference continues, the motion-compensated predicted image at the time of encoding and the motion-compensated predicted image at the time of decoding are The difference becomes large, and the error becomes conspicuous on the contrary. Therefore, an example of an encoding device suitable for the decoding device as shown in FIG. 3 will be described with reference to FIG.

FIG. 7 shows an example in which the decoding system shown in FIG. 3 is used in the local decoder in the conventional moving picture compression system shown in FIG. In the figure, the prediction error signal from which the motion compensation inter-frame prediction image is subtracted by the difference circuit 1 is encoded by the DCT circuit 2, the quantization circuit 3, and the encoding circuit 4.
On the other hand, the quantization result is the inverse quantization circuit 5 and the inverse DCT circuit 6
Are decoded and supplied to the distortion removal processing circuit 9.
The characteristics of the distortion removal processing at this time are determined in the decision circuit 10 in the same manner as in the case of the decoding apparatus described above. Then, the distortion removal processing result is added by the adder circuit 7 to the motion-compensated inter-frame predicted image.

Then, the motion compensation prediction circuit 8 having a built-in image memory having a variable delay function for motion compensation calculates a motion vector and creates a motion-compensated inter-frame predicted image of the next frame.

Although not shown in FIGS. 3 and 4, in the image compression method using this apparatus, intra-frame compression is inserted at constant frame intervals, but at that time, the signal from the motion compensation prediction circuit 8 is not used. That is, 8 in the motion compensation prediction circuit
Memory has been reset.

[0038]

As described in detail above, according to the present invention,
With a simple circuit, distortion can be removed at high speed without causing blurring in the image.

[Brief description of drawings]

FIG. 1 is a diagram showing a sigma filter for removing mosquito noise according to a first embodiment of the present invention.

FIG. 2 is a diagram showing an arrangement of DCT coefficients in an 8 × 8 block.

FIG. 3 is a circuit configuration diagram for realizing a distortion removal process according to a second embodiment of the present invention.

FIG. 4 is a diagram showing a configuration of an encoding device suitable for the decoding device shown in FIG.

FIG. 5 is a block diagram showing a conventional moving image compression method using inter-frame correlation.

FIG. 6 is a diagram for explaining an operation of compressing a still image by a coding method using DCT.

[Explanation of symbols]

11 ... Variable length code decoding circuit, 12 ... Inverse quantization circuit, 13
... Inverse DCT circuit, 14 ... Addition circuit, 15 ... Motion compensation prediction circuit, 16 ... Distortion removal processing circuit, 17 ... Image output unit, 1
8 ... Judgment circuit.

Claims (1)

[Claims] 1. An image signal decoding device for decoding image data compressed by block-wise orthogonal transformation, quantization, and variable length coding, wherein the image data obtained by the decoding is Based on at least one of a motion vector and block type information for each block, and a distortion removal characteristic of the distortion removal processing means for removing distortion by performing distortion removal processing means for removing distortion. An image signal decoding apparatus, comprising: a determining unit that changes each block for each block.