Image Contrast Enhancement Using Histogram Equalization Techniques: Review

Image contrast enhancement is a fundamental pre-processing step in application requiring image processing operations. Histogram Equalization (HE) method is widely used for contrast enhancement. However, HE is not suitable for consumer electronic products directly. As a result, such image creates side-effects such as washed out appearance and false contouring due to the significant change in brightness. In order to overcome these problems, mean brightness preserving HE based techniques have been proposed. Generally, these methods partition the histogram of the original image into sub histograms and then independently equalize each sub histogram with Histogram Equalization. This paper presents a review of different popular histogram based techniques proposed for gray scale static images. Major difference among the methods is only the criteria used to divide the input histogram. Comparative analysis of different enhancement will be carried out. In order to evaluate, the performance of these techniques are examined on the basis of AIC (Average Information Content), CII (Contrast Improvement Index), AMBE (Absolute Brightness Error). Comparisons with the best available results are given in order to illustrate the best possible technique that can be used as powerful image enhancement. Keywords— Contrast enhancement, Histogram equalization, Histogram Partition, image enhancement, Brightness preservation, Average Information Content, Contrast Improvement Index, Absolute Brightness Error.