Adaptive partition compression and perception-based video compression method

Abstract

The invention provides an adaptive partition compression and perception-based video compression method. The method comprises two steps, namely the step of adaptively partitioning video images, and classifying and assigning sampling rates for various image blocks. During the step of adaptively partitioning video images, a gray difference value between the adjacent pixels of a reference frame image is adopted as a basis for block size segmentation, and a partitioning threshold value T is set. The gray average difference value between the adjacent pixels of a current region block is compared with the threshold value, and the adaptive blocks of the video image are partitioned based on the quad-tree algorithm. In this way, flat regions are effectively separated from detail regions and edge regions. On the basis of the adaptive partitioning operation, an inter-frame difference value for the DCT coefficients of video pixels is adopted as a basis for partitioning, and various image blocks diversified in size are divided into three types, namely quickly changing blocks, transition blocks and slowly varying blocks. Meanwhile, appropriate sampling rates are assigned to different types of image blocks. The method is good in video reconstruction quality and short in reconstruction time. Under the same condition, the video reconstruction quality and the reconstruction time of the above method are better than those of the video uniform partitioning, compression and perception processing method.

Description

technical field [0001] The invention belongs to the field of video processing. The compressive sensing theory is used in video compression processing, so that signal sampling and compression can be combined, effectively solving the limitation of the Nyquist sampling theorem on the number of data collection, and "sampling first, then sampling" in conventional video compression. Data resource waste caused by "compression" and other issues. Background technique [0002] There is a high degree of redundancy between adjacent pixels in each frame of the video sequence and between corresponding pixels in the inter-frame images. The video compression coding standard uses high-speed sampling of image data, which is predicted, transformed, Encoding and other processing, discarding most redundant data to achieve the purpose of compression. The compressed sensing processing method combines sampling and compression, and makes the number of measurements break through the limitation of th...

AI Technical Summary

Problems solved by technology

However, uniform partitioning cannot reflect the characteristics of different video content, and there is a problem that the flat area is too small, while the details and edge areas are too large, which affects the quality of video reconstruction and the time required for reconstruction.

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