Compressive sampling (CS), or “Compressed Sensing,” has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively...
We consider the problem of classification of a pattern from multiple compressed observations that are collected in a sensor network. In particular, we exploit the properties of r...
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as d...
Nikhil S. Rao, Robert D. Nowak, Stephen J. Wright,...
In this paper, a new approach for Confocal Microscopy (CM) based on the framework of compressive sensing is developed. In the proposed approach, a point illumination and a random ...
Traditionally, video acquisition, coding and analysis have been designed and optimized as independent tasks. This has a negative impact in terms of consumed resources, as most of ...
M. Cossalter, Giuseppe Valenzise, Marco Tagliasacc...