A fuzzy histogram weighting method for efficient image contrast enhancement

Image contrast enhancement is an important step in digital image processing applications. In this paper, we present an efficient contrast enhancement approach, which employs a histogram weighting method based on fuzzy system. It is able to enhance the contrast of input images while preserving their details. The proposed method divides the histogram of the original image into three sub-histograms using Fuzzy clustering. The obtained sub-histograms are weighted based on the Mamdani Fuzzy inference system, and then they are summed to generate a new histogram. The produced histogram is modified to reduce undesirable effects of its spikes and pits. Finally, the enhanced image is obtained by equalization of the modified histogram. The Mamdani fuzzy inference system assigns an appropriate dynamic range to each input interval of gray levels (sub-histogram), hence enhancing the image details. Experimental results for different types of images verified the merit of the proposed method in terms of preservation the input image details and improving its contrast.