Fuzzy Domain Modified Histogram Equalisation in Medical Image Contrast Enhancement Technique
Recently medical images are considered as one of the most widely utilised tools for diagnostic disease in the field of medical science. Most of the medical images are suffering from poor contrast due to the inadequate lighting or signal during acquisition. So as to make more convenient to diagnose disease, it is required to enhance the poor contrast. This paper presents a fuzzy domain modified weighted histogram equalization algorithm for medical image contrast enhancement. In this algorithm, the input image histogram is fuzzyfied and normalized first. In the next step, the normalized histogram is modified by manipulating only the valley points with a transforming function. After that, the modified histogram is again fuzzyfied and normalized. The cumulative distribution function (CDF) is generated from the normalized histogram. Once the CDF is generated, weighted histogram equalization is applied to generate the output image as the last step. This algorithm is tested on medical images of many forms measuring its performance through objective as well as subjective techniques. From the result, it is observed that this algorithm outperforms over other conventional histogram equalization methods both in terms of subjective and objective observation.
Keywords - Medical Image, Fuzzy Histogram, Histogram Equalization, Modified CDF and Weighted Histogram Equalization.