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Iterative image reconstruction of data measured by a Compton scattering camera has to overcome various difficulties, e.g., large amount of data, noise arising from both low counts recorded, and the imaging response. Image estimation by the Maximum Likelihood (ML) criterion induces noise amplification, so a denoising step is needed. The proposed solution is a denoising technique using wavelet-based...
The objective of image denoising is to remove the noises and to retain important image features as much as possible. Linear approaches could be effective for some simple cases with slowly varying noises, but not for other slowly varying noise cases and rapidly varying noise cases. As a nonlinear wavelet based technique, the wavelet thresholding is effective to denoise blurring aerial images. Either...
Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of scattering phenomena. This paper presents a despeckling method for SAR images based on adaptive bandelets thresholding. This threshold is derived in a Bayesian framework. The proposed threshold is simple and closed form, and it is applied to adaptive bandelets coefficients...
Complexity of noisy engineering or biological data often involves non-stationarity, non-gaussianity, long memory, self-similarity, multi-scale structure, etc. In application of wavelet based statistical methods to analyze these types of data it is of importance to know how the choice of wavelet basis function and the noise level contained in the signals affect the performance of a de-noising method...
According to the characters of CE signal, improved wavelet thresholding with translation invariant was described to denoise for microchip capillary electrophoresis in this paper. The improved thresholding function has muti-derivative compared with the soft thresholding. The denoising method can not only remain the geometrical characteristics and keep the amplitudes of the original electrophoresis...
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