Comparative evaluation of denoising methods on brain CT images Online publication date: Fri, 13-Sep-2013
by H.S. Bhadauria; M.L. Dewal
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 6, No. 3, 2013
Abstract: The purpose of the paper is to carry out a comparative assessment of different denoising methods, namely, Wiener filter, Median filter, Anisotropic Diffusion (AD), Wavelet-based method, Total Variation (TV) and Curvelet-based method, on brain CT images. The focus of this work is to compare these methods not only for the suppression of noise but also for the preservation of edges on brain CT images. The experimental results show that the curvelet-based denoising method shows the best performance, followed by the Wiener filter in terms of perceptual quality, noise suppression and edge preservation. However, the curvelet-based denoising method generates visual distortion in the homogenous regions. TV method induces staircase effect and loss the fine details. The wavelet-based method yields better denoising, particularly in homogenous regions, but does not gives better results in edgy regions, while AD shows the maximum blurring effects.
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