We perform a statistical analysis of curvelet coefficients, distinguishing between two classes of coefficients: those that contain a significant noise-free component, which we call...
Linda Tessens, Aleksandra Pizurica, Alin Alecu, Ad...
The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data [1,2]. Multiwavelets, wavelets with several scaling ...
In this paper, we propose a fast image deconvolution algorithm that combines adaptive block thresholding and Vaguelet-Wavelet Decomposition. The approach consists in first denoisi...
We propose a new wavelet-based method for im age denoising that applies the Bayesian framework, using prior knowledge about the spatial clustering of the wavelet coefficients. Loc...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
De-noising of SPECT and PET images is a challenging task due to the inherent low signal-to-noise ratio of acquired data. Wavelet based multiscale denoising methods typically apply ...
Yinpeng Jin, Elsa D. Angelini, Peter D. Esser, And...