No Reference Image Quality Algorithm based on Human-Eye Sensitive Conception for Contrast-Distortion Evaluation

Abstract

No reference image quality assessment IQAs algorithms are widely used for finding distortions in images without comparing them to references. Image' areas with no details may indicate a brightness saturation change, as well as the presence of noise in the background, which are more visible types of distortions. Thus, the design of such IQA should take into account the human visual conception. This paper proposes a no-reference image quality evaluation algorithm that takes into account the finest edge detection process and entropy deployment in regard to human visual sensitive HVS to quantify brightness saturation variations and noise in pixels. Statistic objective metrics for correlation coefficient which person PCC, spearman rank order SROCC, Root Mean Squared Error RMSE are used in the objective evaluation in corresponding with the subjective evaluation. The proposed algorithm is tested and significantly has well correlation PCC > 0.87, SROCC > 0.91, RMSE < 0.34. The findings of this research could be used to improve the performance of no-reference HVS-based IQA algorithms currently in use.