无需学习的无参考彩色噪声图像质量评价方法

doi:10.11896/jsjkx.190900051

Abstract

Abstract: Noise is one of the most common and varied types of distortion,but there are few studies on the noise types other than Gaussian noise.This paper proposed a non-reference color noise image quality assessment method that can evaluate five kinds of noise types without learning.The method is based on the quaternion singular value decomposition,and uses the relationship between the area enclosed by the reciprocal singular value curves of the image and the degree of the image distortion to derive a quality index.The method almost requires very little prior knowledge of any image or distortion nor any process of training.Experimental results on four simulated databases show that the proposed algorithm delivers quality predictions that have high correlation with human subjective judgments,and achieves better performance in comparison with the relevant state-of-the-art full-refe-rence and non-reference quality metrics.

Key words: Image quality assessment, No-reference, Quaternion singular value decomposition, Reciprocal singular value curve

CLC Number:

TP391

YANG Yun-shuo, SANG Qing-bing. No-reference Color Noise Images Quality Assessment Without Learning[J].Computer Science, 2020, 47(10): 161-168.

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No-reference Color Noise Images Quality Assessment Without Learning

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