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A Quality Assessment tool for Performance Measurement of Image Contrast Enhancement Methods

Abdoli, Mohsen and Nasiri, Fatemeh and Brault, Patrice and Ghanbari, Mohammed (2019) 'A Quality Assessment tool for Performance Measurement of Image Contrast Enhancement Methods.' IET Image Processing, 13 (5). pp. 833-842. ISSN 1751-9659

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Abstract

An objective image quality assessment tool is proposed to measure image enhancement quality with emphasis on contrast. In the proposed tool, which is based on maximizing contrast with minimum artefact (MCMA), local and global properties of an image are measured through pixel-wise and histogram-wise features, respectively. To this aim, three sub-measures are introduced, each of which able to detect one contrast-related quality aspect: (i) low dynamic range of image; (ii) histogram shape preservation during image enhancement process; and (iii) local pixel diversity. These sub-measures are combined through a subjective test to adapt them to the mean opinion scores (MOSs) of a diverse set of training contrast-enhanced images. A regression algorithm performs the adaptation by fitting the three sub-measures to the MOS values and finding an optimal linear combination by maximizing the Pearson correlation. In order to evaluate the performance of the MCMA algorithm, another independent, subsequent, subjective test was performed on a set of images enhanced by various known contrast enhancement algorithms to obtain MOS values and to compare them with the output of the proposed MCMA method. The experimental results show that MCMA has the highest correlation to the MOS when compared to the existing tested contrast measurement tools.

Item Type: Article
Uncontrolled Keywords: regression analysis; image enhancement; feature extraction; Pearson correlation; regression algorithm; mean opinion scores; maximising contrast minimum artefact; tested contrast measurement tools; contrast enhancement algorithms; subsequent test; independent test; MCMA algorithm; optimal linear combination; MOS values; training contrast-enhanced images; local pixel diversity; histogram shape preservation; low dynamic range; contrast-related quality aspect; histogram-wise features; image enhancement quality; objective image quality assessment tool; image contrast enhancement methods; performance measurement; MCMA method
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 26 Mar 2019 11:30
Last Modified: 06 Jan 2022 13:59
URI: http://repository.essex.ac.uk/id/eprint/24261

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