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A blur insensitive structural similarity for image quality assessment ZHENG Deª²pin, SHEN Haiª²bin, ZHAO Wuª²feng £¨Institute of VLSI Design, Zhejiang University, Hangzhou 310027, China£© Abstract: Considering different texture has different sensitivity for human eyes, a blur insensitive structural similarity model(WSSIM) was proposed, which based on edge to partition different weight region. Experimental comparisons with PSNR, SSIM and MS_SSIM on the LIVE database show that this appoach is simple to calculate, the performance is more excellent than PSNR,SSIM and better than MS_SSIM. Key words: peak signalª²noise ratio (PSNR); structural similarity (SSIM); multiª²scale structural similarity (MS_SSIM); image quality assessment (IQA); human visual system (HVS)
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