Blind image quality evaluation using the conditional histogram patterns of divisive normalization transform coefficients

Ying Chu; Xuanqin Mou; Hengyong Yu

doi:10.1117/12.2271682

19 September 2017 Blind image quality evaluation using the conditional histogram patterns of divisive normalization transform coefficients

Ying Chu, Xuanqin Mou, Hengyong Yu

Author Affiliations +

Proceedings Volume 10396, Applications of Digital Image Processing XL; 103961V (2017) https://doi.org/10.1117/12.2271682
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

A novel code book based framework for blind image quality assessment is developed. The code words are designed according to the image pattern of joint conditional histograms among neighboring divisive normalization transform coefficients in degraded images. By extracting high dimensional perceptual features from different subjective score levels in the sample database, and by clustering the features to their centroids, the conditional histogram based code book is constructed. Objective image quality score is calculated by comparing the distances between extracted features and the code words. Experiments are performed on most current databases, and the results confirm the effectiveness and feasibility of the proposed approach.

Citation Download Citation

Ying Chu, Xuanqin Mou, and Hengyong Yu "Blind image quality evaluation using the conditional histogram patterns of divisive normalization transform coefficients", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103961V (19 September 2017); https://doi.org/10.1117/12.2271682

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