DocumentCode :
458984
Title :
Image Denoising Based on A New Wavelet Statistical Model
Author :
Wang, Xili ; Wang, Xiyuan ; Cao, Han
Author_Institution :
Coll. of Comput. Sci., Shaanxi Normal Univ, Xi´´an
Volume :
2
fYear :
2006
fDate :
16-18 Oct. 2006
Firstpage :
342
Lastpage :
346
Abstract :
A new image denoising algorithm is proposed. It models wavelet coefficients as Laplacian distribution. An exponential type a prior distribution is defined for the Laplacian distribution parameter. The image wavelet coefficients can be regarded as a realization of a doubly stochastic process. Then one can use maximum a posterior (MAP) estimator and spatial adaptive technique to estimate the distribution parameter and the clean coefficients. The method is realized with an over complete transform known as dual tree complex wavelet transform (DT-CWT). Experiments demonstrate the effectiveness and low complexity of the new algorithm
Keywords :
Laplace transforms; computational complexity; image denoising; maximum likelihood estimation; statistical distributions; stochastic processes; trees (mathematics); wavelet transforms; Laplacian distribution; dual tree complex wavelet transform; image denoising; maximum a posterior estimator; spatial adaptive technique; stochastic process; wavelet statistical model; Computer science; Discrete transforms; Discrete wavelet transforms; Educational institutions; Hidden Markov models; Image denoising; Laplace equations; Parameter estimation; Wavelet coefficients; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
Type :
conf
DOI :
10.1109/ISDA.2006.253859
Filename :
4021686
Link To Document :
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