A Method for Mammographic Image Denoising Based on Hierarchical Correlations of the Coefficients of Wavelet Transforms

Abstract

In this work the authors present an effective denoising method to attempt to reduce the noise in mammographic images. The method is based on using hierarchical correlation of the coefficients of discrete stationary wavelet transforms. The features of the proposed technique include iterative use of undecimated multi-directional wavelet transforms at adjacent scales. To validate the proposed method, computer simulations were conducted, followed by its applications to clinical mammograms. Mutual information originating from information theory was used as an evaluation measure in the present study. Moreover, we conducted a perceptual evaluation of the processed images obtained from the proposed method and other conventional methods for confirmation of the effectiveness of the proposed approach. The experimental results show that our proposed method has the potential to effectively reduce noise while maintaining high-frequency information of original images.