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Proceedings Paper

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

Paper Details

Date Published: 19 September 2017
PDF: 10 pages
Proc. SPIE 10396, Applications of Digital Image Processing XL, 103961V (19 September 2017); doi: 10.1117/12.2271682
Show Author Affiliations
Ying Chu, Shenzhen Univ. (China)
Xuanqin Mou, Xi'an Jiaotong Univ. (China)
Hengyong Yu, Univ. of Massachusetts Lowell (United States)

Published in SPIE Proceedings Vol. 10396:
Applications of Digital Image Processing XL
Andrew G. Tescher, Editor(s)

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