A reference-free image quality assessment method based on saliency regions
Chen Xu, Jingfeng Zang, Shengsui Zhang · 2022
In order to effectively evaluate the quality score of blurred images, a reference-free blurred image quality evaluation method based on saliency regions is proposed. The method first calculates the saliency value of the image through the improved SDSP algorithm, and uses the improved adaptive threshold to binarize the image to extract the saliency region of the image; then, the image is re-blurred with a Gaussian low-pass filter to obtain the reference image, At the same time, the similarity of the blur detection probability of the salient region of the image before and after re-blurring and the similarity of the standard deviation of the image before and after re-blurring are calculated; finally, the two are fused to obtain the final evaluation result of the image. Compared with the recognized excellent evaluation methods in the LIVE and CSIQ image databases, the comparison results show that the algorithm in this paper is superior to the traditional excellent evaluation methods, and has high versatility and accuracy.