Performance of Various Wavelets for Denoising and Contrast Enhancement of Digital Mammograms

摘要

Image denoising and enhancing the contrast by means of wavelet transforms has been an active research topic for many years. For a given noisy image, the kind of wavelet used has significant impact on the quality of the denoised image. There are mainly three major steps in the denoising and image enhancement algorithm based on wavelet transform. Firstly, decompose the noisy image into wavelet domain using a specific wavelet transform in order to obtain wavelet coefficients. Secondly, adjust the wavelet coefficients to remove noise and emphasize features. Thirdly, apply the inverse wavelet transform to map the result to the space domain in order to achieve denoising and enhancing image. Wavelet transform uses a large variety of wavelets for decomposition of images. Each has its own technical advantages. The wavelet transform results therefore have some advantages which depend on the type of wavelet used. In this paper, different wavelets have been used to perform the transform of mammogram images and their results have been discussed and analyzed. The analysis has been carried out in term of PSNR (peak signal-to-noise ratio) obtained and time taken for decomposition of noisy images and reconstruction to obtain denoise images. This analysis will help to select the suitable wavelet for denoising and enhance the contrast of noise corrupted mammograms images. The results of this study are quite promising.