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Spatiotemporal wavelet maximum a posteriori estimation for video denoising

[+] Author Affiliations
Pavel A. Khazron, Ivan W. Selesnick

Polytechnic Institute of New York University, 6 Metrotech Center, Brooklyn, New York 11201

J. Electron. Imaging. 19(4), 043015 (December 06, 2010). doi:10.1117/1.3514739
History: Received March 17, 2010; Revised August 02, 2010; Accepted September 21, 2010; Published December 06, 2010; Online December 06, 2010
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We examine one way to extend recently proposed wavelet-based maximum

aposteriori estimation rules for image denoising to video. The proposed approach takes into account both spatial and temporal dependencies between wavelet coefficients, and is general enough to incorporate different spherically contoured prior distributions on noiseless coefficients, as well as different spatiotemporal coefficient neighborhoods. Presented extensions of the algorithm have reasonable complexity and are suited to vectorized, convolution-based implementations.

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© 2010 Society of Photo-Optical Instrumentation Engineers

Topics

Denoising ; Video ; Wavelets

Citation

Pavel A. Khazron and Ivan W. Selesnick
"Spatiotemporal wavelet maximum a posteriori estimation for video denoising", J. Electron. Imaging. 19(4), 043015 (December 06, 2010). ; http://dx.doi.org/10.1117/1.3514739


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