Contrast Enhancement of Mammograms Images Based on Hybrid Processing

This paper introduces a new enhancement algorithm based on combination of different processing techniques. The method uses different methods at different stages of processing. In the beginning input image given to the algorithm is a portable gray map image and then Gaussian low pass filter is used to decompose the input image into low and high frequency components. On low frequency components we apply mathematical morphological operations and on high frequency components we apply edge enhanced algorithm. After this we combine processed low and high frequency components to get an enhanced image. Enhanced image is having better contrast and edge visibility comparing to the original image, but it contains noises. Wavelet transform is used to denoise the noisy image. The denoised image is then processed by using contrast limited adaptive histogram equalization(CLAHE) to have better edge preservation index (EPI) and contrast improvement index (EPI). The resulting image is then smoothed by passing the output image through a guided image filter(GIF).The edge preserve capacity and preservation of the naturalness of the GIF allows us to get better results.