The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement

Proper contrast change can improve the perceptual quality of most images, but it has largely been overlooked in the current research of image quality assessment (IQA). To fill this void, we in this paper first report a new large dedicated contrast-changed image database (CCID2014), which includes 65...

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Bibliographic Details
Published inIEEE transactions on cybernetics Vol. 46; no. 1; pp. 284 - 297
Main Authors Gu, Ke, Zhai, Guangtao, Lin, Weisi, Liu, Min
Format Journal Article
LanguageEnglish
Published United States IEEE 01.01.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Proper contrast change can improve the perceptual quality of most images, but it has largely been overlooked in the current research of image quality assessment (IQA). To fill this void, we in this paper first report a new large dedicated contrast-changed image database (CCID2014), which includes 655 images and associated subjective ratings recorded from 22 inexperienced observers. We then present a novel reduced-reference image quality metric for contrast change (RIQMC) using phase congruency and statistics information of the image histogram. Validation of the proposed model is conducted on contrast related CCID2014, TID2008, CSIQ and TID2013 databases, and results justify the superiority and efficiency of RIQMC over a majority of classical and state-of-the-art IQA methods. Furthermore, we combine aforesaid subjective and objective assessments to derive the RIQMC based Optimal HIstogram Mapping (ROHIM) for automatic contrast enhancement, which is shown to outperform recently developed enhancement technologies.
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ISSN:2168-2267
2168-2275
DOI:10.1109/TCYB.2015.2401732