Abstract: Image denoising is one of the most significant tasks especially in medical image processing, where the original images are of poor quality due the noises and artifacts introduces by the acquisition systems. In this paper, we propose a new image denoising scheme by modifying the wavelet coefficients using soft-thresholding method, we present a comparative study of different wavelet denoising techniques for CT images and we discuss the obtained results. The denoising process rejects noise by thresholding in the wavelet domain. The performance is evaluated using Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE). Finally, Gaussian filter provides better PSNR and lower MSE values. Hence, we conclude that this filter is an efficient one for preprocessing medical images.

Lubna Gabralla, Hela Mahersia and Marwan Zaroug, “Denoising CT Images using wavelet transform” International Journal of Advanced Computer Science and Applications(IJACSA), 6(5), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060520

@article{Gabralla2015,
title = {Denoising CT Images using wavelet transform},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060520},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060520},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {5},
author = {Lubna Gabralla and Hela Mahersia and Marwan Zaroug}
}