Abstract:At present, the existing general no-reference image quality assessment methods are used for special purpose. Furthermore, the distortion type of the image is unknown in practical application. Most of no-reference image quality assessment methods are based on the geometrical description feature of image, but this type of method relies on the boundary of image too much. To solve this problem, a no-reference image quality assessment method was proposed based on the gradient similarity decomposition of image, which was named Decomposition of Gradient Similarity (DGS). The proposed method extracted the gradient feature and decomposed the correlation of gradient as the main structure information of the image. The experimental results show that the proposed DGS model is better than Peak Signal-to-Noise Ratio (PSNR) (or Mean Square Error (MSE)) model, which is more sensitive to Human Visual System (HVS) characteristics and more consistent to the subjective evaluation value.
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