23 March 1994 Generalized image contrast enhancement technique based on Heinemann contrast discrimination model
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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.
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Hong Liu, Hong Liu, Calvin F. Nodine, Calvin F. Nodine, } "Generalized image contrast enhancement technique based on Heinemann contrast discrimination model", Proc. SPIE 2182, Image and Video Processing II, (23 March 1994); doi: 10.1117/12.171068; https://doi.org/10.1117/12.171068
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