Mammogram Image Enhancement Using Entropy and CLAHE Based Intuitionistic Fuzzy Method

Mortality rate because of breast cancer diminishes to a large extent if the categorization of breast lesions as malignant or benign is done properly. But this process is quite complicated owing to erroneous detection of noise pixels as false positives. It can be reduced by proper enhancement of the features of the mammogram giving an indication of cancer. In this paper, contrast limited adaptive histogram equalization (CLAIM) and entropy-based intuitionistic fuzzy method are anticipated for improving the contrast of digital mammogram images. To validate the efficacy of the proposed algorithm over type II fuzzy set-based techniques, subjective, quantitative and visual evaluation is done on publicly available MIAS database. Experimental results prove that the proposed technique gives better visual quality. It provides high values of subjective and quantitative metrics compared to several states of art algorithms.