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

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.