Authors: G. Jagadeeswar Reddy, T. Jaya Chandra Prasad, M.N. Giri Prasad
Addresses: SVIST, Tadigotla, Kadapa-516003, A.P., India. ' RGMCET, Nandyal-518502, Kurnool, A.P., India. ' JNTUCE, Pulivendula-51502, Kadapa, A.P., India
Abstract: A new system of multi-scale transform, namely, the curvelets, was developed recently, which possess directional features and provides optimally sparse representation of objects with edges. In this paper a novice algorithm for image denoising based on lossy compression and curvelet thresholding (LCCT) is proposed. The results are compared with the results obtained from denoising methods like wavelets (DWT), lossy compression and wavelet thresholding (LCWT) and curvelets (DCvT). Standard deviation and PSNR are selected as performance metrics and it is shown that the proposed algorithm outperforms the existing algorithms.
Keywords: image denoising; wavelets; curvelets; multi-scale transform; lossy compression; wavelet thresholding.
International Journal of Information and Communication Technology, 2009 Vol.2 No.1/2, pp.41 - 49
Published online: 11 Jun 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article