Existing wavelet-based image denoising techniques all assume a probability model of wavelet coefficients that has zero mean, such as zero-mean Laplacian, Gaussian, or generalized ...
The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on ...
Abstract. This paper proposes a new adaptive wavelet-based Magnetic Resonance images denoising algorithm. A Rician distribution for background-noise modelling is introduced and a M...
This paper exploits the interband correlations of color and multispectral images for wavelet-based denoising. For this, a multispectral extension of the linear minimum mean square...
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...