DocumentCode :
2450036
Title :
Image fusion using adaptive dual-tree discrete wavelet packets based on the noise distribution estimation
Author :
Liu Fang ; Yang Biao ; KaiGang Li
Author_Institution :
Sch. of Electron. Inf. & control Eng., Beijing Univ. of Technol., Beijing, China
fYear :
2012
fDate :
16-18 July 2012
Firstpage :
475
Lastpage :
479
Abstract :
The image fusion algorithm based on adaptive dual-tree discrete wavelet packets(ADDWP) which combine the dual-tree discrete wavelet transform(DDWT) and the wavelet packets is proposed in this paper. In ADDWP, DDWT subbands are further decomposed into wavelet packets with anisotropic decomposition, so that the resulting wavelets have elongated support regions and more orientations than DDWT wavelets. To determine the decompoisition structure, we using the signal-to-noise ratio to estimate the distributing of the denoising in order to search the more denoising subbands to decomposition it again. So we can get adaptive decompoisition structure of wavelet packets. The new algorithm has significantly lower computational complexity. The proposed fusion scheme gives better performance.
Keywords :
computational complexity; discrete wavelet transforms; estimation theory; image denoising; image fusion; trees (mathematics); ADDWP; DDWT subbands; DDWT wavelet packets; adaptive decompoisition structure; adaptive dual-tree discrete wavelet packets; anisotropic decomposition; computational complexity; denoising subbands; image fusion algorithm; noise distribution estimation; signal-to-noise ratio; Discrete wavelet transforms; Noise; Noise reduction; Wavelet coefficients; Wavelet packets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2012 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-0173-2
Type :
conf
DOI :
10.1109/ICALIP.2012.6376664
Filename :
6376664
Link To Document :
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