Contrast Enhancement of Images through Skewness and Mode Based Bi-Histogram Equalization

In this paper, skewness and mode-based histogram equalization algorithm have been proposed for contrast enhancement of digital images. The present method gives a novel idea for histogram clipping and histogram bifurcation. The prior is done with the skewness value and the latter is done with help of mode values of the intensity level random data set. The pixel intensity levels are random and thus a stochastic approach has been used and found to yield improved figure of merits. The image histogram has been clipped with the help of a pre-assigned threshold value computed from skewness value to restrict the rate of over enhancement. The clipped histogram is subdivided into two parts, using the histogram subdivision limit which is calculated on the basis of the mode value of the image. Histogram of individual sub-image is equalized independently and then integrated to form the final enhanced image. The simulation results have shown that the proposed skewness and mode based bi-histogram equalization algorithm enhances the contrast of the image in a better manner compared with the other histogram equalization methods in terms of FSIM, PSIM, SFF, VSI, HaarPSI, and GMSD.