Image denoising based on adaptive fusion of curvelet transform and Total Variation. (3rd January 2012)

• Record Type: Journal Article
• Authors: Bhadauria, H.S.; Dewal, M.L.
• Is Part Of: International journal of signal and imaging systems engineering. Volume 4:Number 4(2011)
• Page Start: 220
• Page End: 227
• Publication Date: 2012-01-03
• Subjects: curvelet transform -- TV -- total variation -- CT -- computed tomography; Signal processing -- Periodicals; Imaging systems -- Periodicals; Information theory -- Periodicals; 621.3822
• Languages: English
• ISSNs: 1748-0698

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.