Histogram Modified Local Contrast Enhancement for mammogram images

Abstract

Early detection of breast cancer in the mammograms is very essential in the field of medicine. Contrast enhancement of mammograms based on Histogram Equalization (HE) is presented. Histogram equalization is an effective and simple technique for contrast enhancement. The standard histogram equalization (HE) usually results in excessive contrast enhancement because of lack of control on the level of enhancement. The Histogram Modified Local Contrast Enhancement (HM-LCE) is introduced in this paper to adjust the level of contrast enhancement, which in turn gives the resultant image a strong contrast and also brings the local details present in the original image for more relevant interpretation. It incorporates a two stage processing both histogram modifications as an optimization technique and a local contrast enhancement technique. This method is tested for Mias mammogram images. The performance of this method is determined using three parameters like Enhancement Measure (EME), Absolute Mean Brightness Error (AMBE) and Discrete Entropy (H) for all 22 numbers of Mias mammogram images with microcalcification. It's enhancement potential is also tested by sobel and otsu methods for the detection of microcalcification in the mammogram image. From the subjective and quantitative measures it is interesting that this proposed technique provides optimum results by giving better contrast enhancement and preserving the local information of the original mammogram images in the Mias data base and the method has increased the detectability of micro calcifications present in the given mammogram image.