81 search results - page 6 / 17 » Reconstruction of sparse signals from distorted randomized m... |
ICASSP
2009
IEEE
15 years 4 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
15 years 10 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
15 years 4 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
14 years 9 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
15 years 11 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...