density-based histogram partitioning and local equalization for contrast enhancement of images

Histogram equalization technique is one of the basic methods available in image contrast enhancement. the use of this method in the case of images with uniform gray levels (with a narrow histogram) causes the loss of image details and the natural look of the image. in order to overcome this problem and to have a better image contrast enhancement, a new two-step method is proposed. in the first step, the image histogram is partitioned into some sub-histograms according to the mean value and standard deviation, which is controlled with the psnr measure. in the second step, each sub-histogram is improved separately and locally with the traditional histogram equalization. finally, all sub-histograms are combined to obtain the enhanced image. the experimental results show that this method would not only keep the visual details of the histogram but also enhance the image contrast.