Regularization techniques have been in use in signal recovery for over four decades. In this paper, we propose a new, synthetic approach to the study of regularization methods in ...
Classical objective criteria evaluate speech quality using one quantity which embed all possible kind of degradation. For speech denoising applications, there is a great need to d...
Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
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...