81 search results - page 6 / 17 » Reconstruction of sparse signals from distorted randomized m... |
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...
ICIP
2009
IEEE
14 years 8 months ago
2009
IEEE
In this work, we propose algorithms to recursively and causally reconstruct a sequence of natural images from a reduced number of linear projection measurements taken in a domain ...
ICIP
2008
IEEE
14 years 1 months ago
2008
IEEE
This paper addresses the image representation problem in visual sensor networks. We propose a new image representation scheme based on compressive sensing (CS) because compressive...
CORR
2006
Springer
2006
Springer
Dense Gaussian Sensor Networks: Minimum Achievable Distortion and the Order Optimality of Separation
13 years 7 months ago
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...