Video compression codec method and codec based on weighted quantization

Abstract

The application discloses a video compression encoding-and-decoding method on the basis of weighting quantification. The encoding-and-decoding process comprises that an attribute component of an image to be encoded is divided into multiple attribute blocks; the attribute blocks are predicted so that residual blocks are obtained, and a transformation coefficient of each frequency point in the residual blocks is obtained after transformation; one default matrix is selected, and weighting calculation is performed on initial quantization step length of the frequency points so that a weighting quantification step length matrix is obtained; and the transformation coefficient is quantified by using the weighting quantification step length matrix so that quantification blocks are obtained, then the quantification blocks are written-in a code stream and other information written-in the code stream is confirmed according to values of the quantification blocks. The application also discloses a video compression encoder-decoder on the basis of weighting quantification. A preset weighting quantification matrix set comprises multiple default matrixes so that transformation coefficient matrixes under different situations can be effectively weighted and quantified, and thus code rate required by encoding can be effectively reduced without reducing subjective quality.

Description

technical field [0001] The present application relates to the field of video data processing, in particular to a weighted quantization-based video compression codec method and codec. Background technique [0002] In the current mainstream video compression codec standard, the residual block generated by the prediction block and the original block needs to be transformed to obtain a transformed block, and the coefficient block obtained after the transformed block is quantized is then stored in the code stream. The process of quantization will cause the distortion of coefficients, resulting in the degradation of image quality. However, the subjective distortions caused by the distortion of the transformation coefficient values ​​at different positions in the transformation block are different. The weighted quantization technology uses this phenomenon to quantize the transform coefficients at different positions with different quantization steps. This technology can reduce th...

AI Technical Summary

Problems solved by technology

This technology can minimize the encoding bit rate without causing a decrease in subjective quality, but using the existing weighted quantization coefficient matrix, the subjective quality is not ideal, and the bit rate required for encoding cannot be effectively reduced

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