Median Adjusted Constrained PDF Based Histogram Equalization for Image Contrast Enhancement

A novel Median adjusted Constrained PDF based Histogram Equalization (MCPHE) technique for contrast enhancement is proposed in this paper. In this method, the probability density function of an image is modified by introducing constraints prior to the process of histogram equalization (HE). This technique of contrast enhancement takes control over the effect of HE so that it enhances the image without causing any loss to its details. A median adjustment factor is then added to the result, which normalizes the change in the luminance level after enhancement. This factor suppresses the effect of luminance change due to the presence of outlier pixels. The outlier pixels of highly deviated intensities have greater impact in changing the contrast of an image. Experimental results show that the proposed method gives better results in terms of PSNR and SSIM values when compared to the existing histogram based equalization methods.