Title: Image denoising based on adaptive fusion of curvelet transform and Total Variation

Authors: H.S. Bhadauria; M.L. Dewal

Addresses: Department of Electrical Engineering, Indian Institute of Technology, Roorkee 247667, India. ' Department of Electrical Engineering, Indian Institute of Technology, Roorkee 247667, India

Abstract: This paper proposed an adaptive denoising approach, which fuses the images denoised by Total Variation (TV), curvelet-based method and edge information. Edge information is extracted from the noise residue of TV method by processing it through curvelet transform. The denoising abilities of the proposed method are evaluated on standard Lena image as well as on brain Computed Tomography (CT) images. Experimental results show that the proposed approach reduces the staircase effect caused by TV method and also reduces fuzzy edges induced by curvelet transform in the homogeneous areas of the image. This proposed adaptive fusion-based approach gives superior results not only for noise suppression but also for edge preservation.

Keywords: curvelet transform; total variation; computed tomography; image denoising; adaptive fusion; image processing; staircase effect; fuzzy edges; noise suppression; edge preservation.

DOI: 10.1504/IJSISE.2011.044537

International Journal of Signal and Imaging Systems Engineering, 2011 Vol.4 No.4, pp.220 - 227

Available online: 30 Dec 2011 *

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