We propose a novel algorithm for denoising Poisson-corrupted images, that performs a signal-adaptive thresholding of the undecimated Haar wavelet coefficients. A Poisson's un...
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
The formation of synthetic aperture radar (SAR) images is formulated as an inverse problem, a flexible approach suitable for a variety of acquisition systems and signal models. T...
This paper presents a signal processing tool for analyzing and manipulating digitized acoustic wave fields, based on a spatio-temporal extension of the time–frequency represent...
The purpose of this paper is to develop an algorithm achieving the performance of fixed-complexity decoder (FSD) with much lower complexity than FSD. An adaptive expansion strate...