Objective video quality assessment method based on chromaticity co-occurrence matrix weighting

Abstract

The invention discloses an objective video quality assessment method based on chromaticity co-occurrence matrix weighting. The method includes the steps that firstly, a quaternion matrix with the dimension being 8*8 is used for describing characteristics, based on the time domain and the space domain, of 8*8 image blocks in a reference image and characteristics, based on the time domain and the space domain, of 8*8 image blocks in a distortion image; then the cosine of an included angle between singular value vectors of the characteristics, based on the time domain and the space domain, of two image blocks, which correspond to each other in position, in the reference image and the distortion image is obtained, and the cosine serves as the difference degree between the two image blocks, which correspond to each other in position, in the reference image and the distortion image; objective assessment values of the image blocks in the distortion image are obtained through the difference degree and weighted values of chromaticity co-occurrence matrixes of the image blocks in the distortion image, and therefore the objective assessment value of the distortion image and the objective assessment value of distortion video are obtained. According to the method, computation complexity in the video assessment process is low, and the relevance between an objective assessment result and subjective perception can be effectively improved.

Description

technical field [0001] The invention relates to a video quality evaluation technology, in particular to an objective video quality evaluation method based on chroma co-occurrence matrix weighting. Background technique [0002] Video or image quality evaluation has important applications in many occasions, such as evaluating the performance of compression algorithms and optimizing compression parameters, monitoring the quality of video transmission in the Internet, and providing QOS services. Therefore, researches on video or image quality evaluation are also increasing. At present, video quality evaluation methods can be divided into two categories: subjective evaluation methods and objective evaluation methods. Subjective evaluation methods are time-consuming and costly, so objective evaluation methods have always been a research hotspot. Objective evaluation methods measure video quality based on quantitative indicators or parameters given by the model. For various objec...

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Problems solved by technology

Traditional objective video quality evaluation methods include mean square error (MSE) method and peak signal-to-noise ratio (PSNR) method, etc., which are widely used because of their low computational complexity and clear physical meaning, but these methods are consistent with subjective vision. poor sex problem

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