An improved structural similarity for image quality assessment

Xiao-zhou Pan; Chun-ling Yang; Sheng-li Xie

doi:10.1117/12.655220

3 November 2005 An improved structural similarity for image quality assessment

Xiao-zhou Pan, Chun-ling Yang, Sheng-li Xie

Proceedings Volume 6044, MIPPR 2005: Image Analysis Techniques; 60441I (2005) https://doi.org/10.1117/12.655220
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

Objective quality assessment has been widely used in image processing for its convenience. Usually human eyes are the terminal of observing images, so many researchers have been studing the objective image quality evaluation method based on Human Visual System (HVS) for decades. Although many methods have been proposed, most of them are based on error sensitivity and are not better than simple PSNR (MSE). Recently the Structural Similarity (SSIM) based on images' structural information is proposed, in which the philosophy is that the HVS is highly adapted to extract structural information from the viewing field, and simulation results have proved it is better than PSNR MSE). By deeply studing SSIM, we find it fails to measure the blurred images with a lot of flat regions and has some shortcomings in its equation. Based on this we propose an improved objective quality assessment method which is called as Gradient-based Structural Similarity (GSSIM). Experiment results show that GSSIM is more consistent with HVS than SSIM and PSNR (MSE).

Citation Download Citation

Xiao-zhou Pan, Chun-ling Yang, and Sheng-li Xie "An improved structural similarity for image quality assessment", Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 60441I (3 November 2005); https://doi.org/10.1117/12.655220

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