Liping Wang, Chengyou Wang, Xiao Zhou, Journal of Information Processing Systems Vol. 13, No. 3, pp. 448-463, Jun. 2017  

https://doi.org/10.3745/JIPS.02.0059
Keywords: Blind Image Quality Assessment (BIQA), Gaussian Blur Image, Saliency Map, Structure Tensor, Structural Similarity (SSIM)
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Abstract

Multimedia is a ubiquitous and indispensable part of our daily life and learning such as audio, image, and video. Objective and subjective quality evaluations play an important role in various multimedia applications. Blind image quality assessment (BIQA) is used to indicate the perceptual quality of a distorted image, while its reference image is not considered and used. Blur is one of the common image distortions. In this paper, we propose a novel BIQA index for Gaussian blur distortion based on the fact that images with different blur degree will have different changes through the same blur. We describe this discrimination from three aspects: color, edge, and structure. For color, we adopt color histogram; for edge, we use edge intensity map, and saliency map is used as the weighting function to be consistent with human visual system (HVS); for structure, we use structure tensor and structural similarity (SSIM) index. Numerous experiments based on four benchmark databases show that our proposed index is highly consistent with the subjective quality assessment.

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