Adaptive partition compression and perception-based video compression method

A block compression sensing and video compression technology, applied in the field of video processing, can solve problems such as too large block, unable to reflect the characteristics of different video content, and affect the quality of video reconstruction. Reconstruction time is short, and the reconstruction time is short , Video reconstruction with good quality effect

CN106941609AActive Publication Date: 2017-07-11ZHEJIANG UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2017-07-11

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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.
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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...

Examples

Embodiment Construction

[0024] The present invention will be further described below in conjunction with the accompanying drawings.

[0025] figure 1 It is a flowchart of a video compression method based on adaptive block compression sensing, specifically including:

[0026] Step 1. Adaptive segmentation of the video image;

[0027] (1.1) Video sequences are grouped, each group takes the first frame as a reference frame, and the remaining frames in the video group carry out the same block according to the adaptive block situation of the reference frame;

[0028] (1.2) Use the gray difference between adjacent pixels of the image frame as the basis for block size segmentation, set the block threshold T; the calculation of the block threshold includes the following steps:

[0029] (1.2.1) For a video image x with a size of n×m pixels, the grayscale of the pixel at position (i, j) is expressed as G i,j , then the average value of the grayscale difference between adjacent pixels in row i and column j ...