NDLI: Quality assessment tool for performance measurement of image contrast enhancement methods

Content Provider	IET Digital Library
Author	Abdoli, Mohsen Nasiri, Fatemeh Brault, Patrice Ghanbari, Mohammad
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.
Starting Page	833
Ending Page	842
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 5, Apr (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5520
Journal	IET Image Processing
Publisher Date	2019-02-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Contrast Enhancement Algorithm Contrast-related Quality Aspect Feature Extraction Histogram Shape Preservation Histogram-wise Feature Image Contrast Enhancement Method Image Enhancement Image Enhancement Quality Image Recognition Independent Test Local Pixel Diversity Low Dynamic Range Maximising Contrast Minimum Artefact MCMA Algorithm MCMA Method Mean Opinion Scores MOS Value Objective Image Quality Assessment Tool Optimal Linear Combination Pearson Correlation Performance Measurement Regression Algorithm Regression Analysis Statistics Subsequent Test Tested Contrast Measurement Tool Training Contrast-enhanced Image
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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