Abstract
Detection of breast cancer in its early stage is very
important in the field of medicine. Optimal Contrast
Enhancement is essential for the detection of mass and micro
calcification in mammogram images. The standard histogram
equalization is effective and simple method for contrast
enhancement but for medical images most of the time it
produces excessive contrast enhancement due to lack of control
for the level of enhancement. In this paper image
enhancement is considered as an optimization problem and
an optimization technique based on entropy and edge
information of the image is presented. The enhancement
function used in the paper is Contrast Limited Adaptive
Histogram Equalization (CLAHE) based on local contrast
modification (LCM). Its enhancement potential is tested by
sobel operator for the detection of microcalcification. Results
are compared with other enhancement techniques such as
Histogram Equalization, Unsharp Masking and CLAHE.
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