Image denoising using non-local means algorithm and subbands mixing

Author

Badran, Ehab F. ; Alhosainy, Ammar M.

Author_Institution

Dept. of Electron. & Commun. Eng., Arab Acad. for Sci. & Technol. & Maritime Transp., Alexandria, Egypt

fYear

2011

fDate

26-28 April 2011

Firstpage

1

Lastpage

10

Abstract

In this paper, an image denoising technique using non-local means algorithm and subbands mixing is proposed. The non-local means algorithm is applied to the noisy image twice with two different spatial filtering parameters then either discrete wavelet transform (DWT) or contourlet transform (CT) is applied to the two resultant images of the non-local means algorithm, then a subbands mixing is preformed to maximize the peak signal to noise (PSNR). The improvement achieved using the proposed technique is about 0.65 dB. Both wavelet and contourlet transforms are used where their improvements are closed to each other and which of them is better varies according the input noisy image.

Keywords

discrete wavelet transforms; filtering theory; image denoising; CT; DWT; contourlet transform; discrete wavelet transform; gain 0.65 dB; image denoising technique; nonlocal mean algorithm; peak signal to noise; spatial filtering parameter; subband mixing; Discrete cosine transforms; Discrete wavelet transforms; Contourlet transform; Image denoising; subband mixing; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Radio Science Conference (NRSC), 2011 28th National

Conference_Location

Cairo

Print_ISBN

978-1-61284-805-1

Type

conf

DOI

10.1109/NRSC.2011.5873625

Filename

5873625