Quadrants Dynamic Fuzzy Histogram Equalization for Color Images with brightness preservation

Contrast enhancement is essential in image processing and contributes to image enhancement. Histogram equalization is perhaps the most common way operators enhance the contrast of digital images. Easy and handy, this method often has too much contrast enhancement, making the output images' visual quality look unnatural. Moreover, it usually cannot also preserve the mean of the image substantially. This paper presents a color image equalization technique that takes a better guess to conserve the brightness. In other words, it is a method based on some image histogram modification using fuzzy and a clipping process for equalization rate applied to the original image. Initially, the histogram is split into two parts hinged on the mean gray level. Then, it is divided into four sections by calculating an average of the two subhistograms. The dynamic equalization is defined for a new range, and the sub-histogram equalization is independent. The simulation results prove that this new method can significantly improve the spatial characteristics of color images and keep a high brightness level