Lossy compression and curvelet thresholding for image denoising

A new system of multiscale 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(WDT), 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.