In this paper a novel method for blind noisy image quality assessment is proposed. First, it is believed that human visual system (HVS) is more sensitive to the local smoothness area in a noise image, an adaptively local homogeneous block selection algorithm is proposed to construct a new homogeneous image named as homogeneity blocks (HB) based on computing each pixel characteristic. Second, applying the discrete cosine transform (DCT) for each HB and using high frequency component to evaluate image noise level. Finally, a modified peak signal to noise ratio (MPSNR) image quality assessment approach is proposed based on analysis DCT kurtosis distributions change and noise level above-mentioned. Simulations show that the quality scores that produced from the proposed algorithm are well correlated with the human perception of quality and also have a stability performance.
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