Lossy compression and curvelet thresholding for image denoising

Author

Reddy, G. Jagadeeswar ; Prasad, T. Jaya Chandra ; GiriPrasad, M.N.

Author_Institution

SVIST, Kadapa

fYear

2008

fDate

1-3 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

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.

Keywords

data compression; image coding; image denoising; wavelet transforms; curvelet thresholding; image denoising; lossy compression; multiscale transform; standard deviation; wavelet thresholding; Continuous wavelet transforms; Frequency; Image coding; Image denoising; Measurement; Noise reduction; PSNR; Propagation losses; Signal to noise ratio; Wavelet transforms; compression; curvelet; denoising; lossy; thresholding; transform; wavelet;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Design, 2008. ICED 2008. International Conference on

Conference_Location

Penang

Print_ISBN

978-1-4244-2315-6

Electronic_ISBN

978-1-4244-2315-6

Type

conf

DOI

10.1109/ICED.2008.4786663

Filename

4786663