A Novel Objective Quality Assessment for Super-Resolution Images
Lei Shu, Yuming Fang, Zhijun Fang, Yong Yang, Fengchang Fei, Naixue N. Xiong · International Journal of Signal Processing Image Processing and Pattern Recognition · 2013
A novel objective quality assessment method is proposed for super-resolution images in this manuscript.We not only estimate the preserved information of each spatial location in the super-resolution image by structural similarity, but also compute the local phase coherence (LPC) with which we can detect the image blur in the super-resolution image.After the preserved structural information and blur information is obtained, an overall evaluation of visual quality of the super-resolution image can be computed.Experimental results show that the proposed objective quality assessment method can be used in the real applications with the original high-resolution images unavailable.