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Proceedings Paper

Image quality optimization via application of contextual contrast sensitivity and discrimination functions
Author(s): Edward Fry; Sophie Triantaphillidou; John Jarvis; Gaurav Gupta
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Paper Abstract

What is the best luminance contrast weighting-function for image quality optimization? Traditionally measured contrast sensitivity functions (CSFs), have been often used as weighting-functions in image quality and difference metrics. Such weightings have been shown to result in increased sharpness and perceived quality of test images. We suggest contextual CSFs (cCSFs) and contextual discrimination functions (cVPFs) should provide bases for further improvement, since these are directly measured from pictorial scenes, modeling threshold and suprathreshold sensitivities within the context of complex masking information. Image quality assessment is understood to require detection and discrimination of masked signals, making contextual sensitivity and discrimination functions directly relevant. In this investigation, test images are weighted with a traditional CSF, cCSF, cVPF and a constant function. Controlled mutations of these functions are also applied as weighting-functions, seeking the optimal spatial frequency band weighting for quality optimization. Image quality, sharpness and naturalness are then assessed in two-alternative forced-choice psychophysical tests. We show that maximal quality for our test images, results from cCSFs and cVPFs, mutated to boost contrast in the higher visible frequencies.

Paper Details

Date Published: 8 February 2015
PDF: 12 pages
Proc. SPIE 9396, Image Quality and System Performance XII, 93960K (8 February 2015); doi: 10.1117/12.2082937
Show Author Affiliations
Edward Fry, Univ. of Westminster (United Kingdom)
Sophie Triantaphillidou, Univ. of Westminster (United Kingdom)
John Jarvis, Univ. of Westminster (United Kingdom)
Gaurav Gupta, Univ. of Westminster (United Kingdom)


Published in SPIE Proceedings Vol. 9396:
Image Quality and System Performance XII
Mohamed-Chaker Larabi; Sophie Triantaphillidou, Editor(s)

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