Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach is based on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid transform is applied to decompose the mammography into different multiscale subband sub-images. In addition, the detail or high frequency sub-images are equalized by the contrast limited adaptive histogram equalization (CLAHE) and low frequency sub-images are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by CLAHE and mathematical morphology. The enhanced image is processed by global non-linear operator in order to obtain natural result. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is contrast evaluation criterion for image, signal-noise-ratio (SNR) and contrast improvement index (CII).