An efficient way to enhance mammogram image using nonsubsampled contourlet transform

Breast cancer is one of the most important causes of increased women death rate in the world. Mammography is the most efficient approach for the early identification of breast diseases. The major objective of mammography is to identify small, non-palpable cancers during its premature stage. On the other hand, mammograms are extremely complicated to interpret being the fact that the pathological transformations of the breast are slight and their visibility is very poor with low contrast and noise. Mammograms has the valuable information such as microcalcifications and masses, which are extremely complicated to identify because mammograms are of low-contrast. Since the mammogram images are very noisy, low-contrast, blur and fuzzy, it is necessary to enhance the mammogram images for accurate identification and early diagnosis of breast cancer. In this paper, proposed an efficient technique to enhance mammogram image using nonsubsampled contourlet transform. The nonsubsampled contourlet transform is built upon nonsubsampled pyramids and nonsubsampled directional filter banks and provides a shiftinvariant directional multiresolution image representation. Existing methods for image enhancement cannot capture the geometric information of images and tend to amplify noises when they are applied to noisy images since they cannot distinguish noises from weak edges. In contrast, the nonsubsampled contourlet transform extracts the geometric information of images, which can be used to distinguish noises from weak edges. Experimental results show the proposed method achieves better enhancement results than other enhancement method.