Image Quality Assessment Based on Local Pixel Correlation

The available image quality assessment methods are mostly based on statistical characteristic and consider very little 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 big effect on the image quality, so a novel image quality assessment based on the pixel correlation is proposed in this paper. Firstly image is parted based on mutual information, and then, three kinds of mutual information between the pixel intensity and the image patches are extracted to catch the variation of the pixel correlation. Finally the machine learning is utilized to learn the mapping from these differences space to image quality. The experimental results show that the proposed framework has good consistency with subjective perception.