Image Contrast Enhancement Using Triple Dynamic Clipped Histogram Equalization

In this paper, a powerful contrast enhancement algorithm based on the histogram equalization, called triple dynamic clipped histogram equalization (TDCHE) is introduced. The proposed method consists of four main processes including partitioning, clipping, mapping and equalization. At first, the input image histogram is partitioned into three portions with a same number of pixels. Next, the histogram clipping process is performed by comparing the clipped threshold level with the average intensities occurred on each sub-histogram. Then, each sub-histogram is mapped to a new dynamic range using simple calculations and finally, equalization process of each histogram is independently accomplished. The proposed TDCHE technique is presented to achieve multiple objectives of maximum average information content (entropy), enhancement ratio control and maintaining the reasonable brightness. In addition, this method leads to a natural enhancement in the output image by providing sharp images, while preserving maximum details far from unnatural phenomena such as intensity saturation and noise enhancement. Evaluation of the proposed TDCHE method performance in terms of information content as well as visual quality shows perceived superiority of the proposed algorithm in comparison to the previously presented methods based on histogram equalization.