一种利用像素局部相关性的图像质量评价方法

doi:10.3969/j.issn.1001-2400.2017.01.017

Abstract

Abstract:

The available image quality assessment methods are mostly based on the statistical characteristic and seldom consider the change of pixel correlation in conjunction with the quality assessment, which induces the quality assessment metric to be limited in the degradation of image quality caused by the change of pixel correlation. However, the pixel correlation change has a great effect on the image quality, so the pixel correlation for image quality assessment is proposed in this paper. Firstly, the mutual information is utilized to segment the image into non-overlapped patches that have a minimum intra-regional diversity and maximum inter-regional diversity, which explores the relationship between segmented patches and image brightness distribution. Secondly, the correlation is described based on the relative entropy, mutual information and conditional entropy, and the image is then abstracted as the specific information, the saliency information and the entanglement information. Finally, the degradations of image information in the distorted image are mapped together to obtain final image quality. Experimental results show that the proposed framework has good consistency with subjective perception.

LU Wen;LI Shuai;XU Hongqiang;HE Lihuo. Local pixel correlation for image quality assessment[J].Journal of Xidian University, 2017, 44(1): 94-99.

References

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Local pixel correlation for image quality assessment

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