A Histogram Modification Framework and Its Application for Image Contrast Enhancement
Arici, T.
Dikbas, S.
Altunbasak, Y.
Dept. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA;
This paper appears in: Image Processing, IEEE Transactions on
Publication Date: Sept. 2009
Volume: 18,
Issue: 9
On page(s): 1921-1935
ISSN: 1057-7149
INSPEC Accession Number: 10816682
Digital Object Identifier: 10.1109/TIP.2009.2021548
First Published: 2009-04-28
Current Version Published: 2009-08-11
Abstract
A general framework based on histogram equalization for image contrast enhancement is presented. In this framework, contrast enhancement is posed as an optimization problem that minimizes a cost function. Histogram equalization is an effective technique for contrast enhancement. However, a conventional histogram equalization (HE) usually results in excessive contrast enhancement, which in turn gives the processed image an unnatural look and creates visual artifacts. By introducing specifically designed penalty terms, the level of contrast enhancement can be adjusted; noise robustness, white/black stretching and mean-brightness preservation may easily be incorporated into the optimization. Analytic solutions for some of the important criteria are presented. Finally, a low-complexity algorithm for contrast enhancement is presented, and its performance is demonstrated against a recently proposed method.
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