| Popis: |
In order to evaluate the perceptual quality of images, a full-reference quality index, which is called principal component deviation (PCD), is presented. This research is motivated by the discovery that the filters learned by the probabilistic principal component analysis are closely resemble the neurons of the human visual system. These filters are used as a model of the visual system, which are trained on 100,000 color image patches of size 4×4 by probabilistic principal component analysis. The PCD relates the image quality with the deviation between two sets of features that extracted by the learned filters. Experimental results show that PCD has relatively low computational complexity and high correlation with subjective quality evaluations. |
