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Bayesian Denoising for Remote Sensing Image Based on Undecimated Discrete Wavelet Transform

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2 Author(s)
Weiling Wang ; Sch. of Sci., Changchun Inst. of Technol., Changchun, China ; Yufeng Li

Because the remote sensing image has a lot of noise in its imaging and transferring, image denoising is an important aspect for its processing. A new Bayesian denoising algorithm for remote sensing image based on undecimated discrete wavelet transform (UDWT) is presented in this paper. The Bayes shrink threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution (GGD). Image denosing is complemented using Donoho's soft-thresholding. Experiment results show that the new algorithm can reduce the artifact, restrain the pseudo-Gibbs phenomena from the orthogonal wavelet transform, and has obvious superiority compared with orthogonal wavelet denoising method.

Published in:

2009 International Conference on Information Engineering and Computer Science

Date of Conference:

19-20 Dec. 2009