A video image decoding and encoding method and device based on area

Abstract

The method comprises: 1) encode step, providing the image data, and selecting area for inputting the digital image; making priority classification for the inputted digital image, and making quantization operation for the transformed image data, and recording the priority data; 2) decode step, decoding the location information and priority information of different areas; calculating the quantization value of each area, and using the quantization value to make inverse quantization operation for the data in each area. The structure of the apparatus thereof is: setting a area selection, priority division and quantization unit in the decode device. The decode device comprises an area information decoding and inversely-quantizing unit.

Description

technical field [0001] The present invention relates to the field of video coding and decoding, in particular to a video coding method and device based on the current region coding method. Background technique [0002] The rapid development of network video streaming services is inevitably restricted by limited bandwidth resources, and when video compression is performed at a very low bit rate, some detailed information is often lost, and even some of the information is of particular interest to people, such as video The head and shoulder area of ​​a person in a meeting, the small target area carrying important information in an aerial image, the interference fringe area in an interferometric multispectral image, and the lesion area in a medical image, etc., can be collectively referred to as an area of ​​interest. From the perspective of subjective vision, the restoration quality of these regions directly affects the overall subjective perception quality of the reconstructe...

AI Technical Summary

Problems solved by technology

These methods have achieved certain results, but none of them can improve the video quality of the region of interest from the perspective of compression, nor can they use the bit rate resources more effectively based on the actual image content.

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