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    Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment

    Manyu Jin1, Tao Wang1, Zexuan Ji1,*, Xiaobo Shen2

    CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 501-515, 2018, DOI: 10.3970/cmc.2018.02371

    Abstract Perceptual image quality assessment (IQA) is one of the most indispensable yet challenging problems in image processing and computer vision. It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation. To further improve the prediction accuracy for the distortion of color images, in this paper, we propose a novel effective and efficient IQA model, called perceptual gradient similarity deviation (PGSD). Based on the gradient magnitude similarity, we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient. The luminance and More >

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