Optimization method for HEVC

Abstract

An optimization method for HEVC comprises the following steps: dividing an original video image into a plurality of mutually independent coding units, namely original image blocks; performing predictive coding, including the steps of removing redundant information and obtaining a predicted image block by adopting an intra-frame prediction mode and an inter-frame prediction mode respectively according to video image time and space redundancy; obtaining a prediction residual error based on the difference value of the image values of the prediction block and the original image block, and carrying out discrete cosine transform and quantization on the prediction residual error; performing entropy coding on the quantized discrete cosine transform coefficient to obtain a compressed code stream of the video sequence, and outputting the compressed code stream; decoding the compressed code stream to obtain a high-resolution video sequence, and performing image interpolation on the high-resolution video sequence to restore the image size of the high-resolution video sequence to the original image size. Under the condition that the video quality is not greatly changed, a coding scheme which is higher in coding efficiency, better in performance and lower in calculation complexity is obtained, and the method is more beneficial to being applied to video transmission and storage in the future.

Description

technical field [0001] The present invention relates to the technical field of video coding, in particular to an optimization method for HEVC high-definition video coding. Background technique [0002] High Efficiency Video Coding (HEVC), also known as H.265, can achieve twice the compression by Blu-ray's best video compression method; however, there are many defects in the existing HEVC encoding technology, such as the following defects: [0003] First, the complexity of HEVC coding is much higher than that of other video coding standards, so the performance is not good under the condition of low bit rate, and the decoded video has serious distortion; [0004] Second, although the compression method based on image downsampling greatly reduces the amount of encoding calculations and eases the pressure on wireless network transmission, this method can be smoother when interpolating flat areas in the image, but it does not affect the smoothness of the image. The interpolation...

AI Technical Summary

Problems solved by technology

[0003] First, the complexity of HEVC coding is much higher than that of other video coding standards, so the performance is not good under the condition of low bit rate, and the decoded video has serious distortion;

[0004] Second, although the compression method based on image downsampling greatly reduces the amount of encoding calculations and eases the pressure on wireless network transmission, this method can be smoother when interpolating flat areas in the image, but it does not affect the quality of the image. The interpolation effect of details such as edges and textures is relatively general, and there are more serious blurring and aliasing effects, resulting in poor visual effects of the reconstructed image;

However, for those 2D images whose internal texture dominance direction is not horizontal or vertical, traditional 2D transforms cannot compress their energy best.

Therefore, neither the DCT nor the DST transformation used in HEVC can take into account the details of the image well.

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