Remote Sensing Image Quality Assessment based on the Ratio of Spatial Feature Weighted Mutual Information

Abstract

Based on the characteristic that the information of remote sensing images varies with the level of image degradation, a new method of remote sensing image quality assessment based on the ratio of spatial feature weighted mutual information is proposed. Firstly, the reference remote sensing image and the distorted image are decomposed using the spatial steerable pyramid. Then the mutual information between the reference remote sensing image and the perceived image through the visual distortion channel is calculated on each scale. Meanwhile the mutual information between the degraded remote sensing image and the perceived image through the visual distortion channel is calculated on each scale. Then the weighting factors of the phase congruency and the location saliency are added to the two calculated mutual information. At last, the spatial feature weighted mutual information of the reference remote sensing image and that of the degraded remote sensing image on each scale is summed up. The ratio of the two is calculated to obtain the global quality index, Remote Sensing Image Quality Assessment Index (RSIQA). Experimental results show that the proposed method has high degree of subjective and objective consistency, and high evaluating effectiveness for the remote sensing images. In addition, it works better than most state-of-the-art IQA indices on the natural images databases.