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Proceedings Paper

Generalized image contrast enhancement technique based on Heinemann contrast discrimination model
Author(s): Hong Liu; Calvin F. Nodine
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Paper Abstract

This paper presents a generalized image contrast enhancement technique which equalizes perceived brightness based on the Heinemann contrast discrimination model. This is a modified algorithm which presents an improvement over the previous study by Mokrane in its mathematically proven existence of a unique solution and in its easily tunable parameterization. The model uses a log-log representation of contrast luminosity between targets and the surround in a fixed luminosity background setting. The algorithm consists of two nonlinear gray-scale mapping functions which have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of gray scale distribution of the image, and can be uniquely determined once the previous three are given. Tests have been carried out to examine the effectiveness of the algorithm for increasing the overall contrast of images. It can be demonstrated that the generalized algorithm provides better contrast enhancement than histogram equalization. In fact, the histogram equalization technique is a special case of the proposed mapping.

Paper Details

Date Published: 23 March 1994
PDF: 11 pages
Proc. SPIE 2182, Image and Video Processing II, (23 March 1994); doi: 10.1117/12.171068
Show Author Affiliations
Hong Liu, Univ. of Pennsylvania (United States)
Calvin F. Nodine, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 2182:
Image and Video Processing II
Sarah A. Rajala; Robert L. Stevenson, Editor(s)

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