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In wavelet-based Bayesian denoising, the performance of several methods strongly depends on the correctness of the distribution that is used to describe the data. Therefore, the selection of a proper model for distribution is thus an important issue in the denoising process. This paper presents a new image denoising algorithm based on bivariate Pearson type VII distribution with approximated MAP estimation...
Wavelet shrinkage denoising has been investigated for a long time due to its simplicity and good results. SLT denoising proposed by Yacov Hel-Or et al. recently generates mapping functions (MFs), also known as shrinkage function, which are learned directly from example images using least-squares fitting. In this paper, we design MFs with the prior information properly incorporated in SLT denoising...
Multi-channel Surface Electromyography (SEMG) always interfere each other while being acquired, which would distort the source SEMG feature. The new method of SEMG processing is put forwarded to eliminate the signal interference between multi-channel SEMG by combining the wavelet transform with the independent component analysis (ICA). In this method, some noise is removed from the raw SEMG first...
In this letter, variational models in pixel domain and wavelet domain are presented for fusion and denoising of noisy multifocus images. In pixel domain, the problem is formulized as minimizing a weighted energy functional, where the total variation (TV) is used as regularity constraint for noise reduction. A new family of weight functions for fusion is proposed that are based on the local average...
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