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ICIP
2007
IEEE
15 years 11 months ago
Compressed Sensing Image Reconstruction Via Recursive Spatially Adaptive Filtering
We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coef?cients of an arbitrary li...
Karen O. Egiazarian, Alessandro Foi, Vladimir Katk...
ICASSP
2010
IEEE
14 years 9 months ago
Reconstruction of sparse signals from distorted randomized measurements
In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown. Assuming just that...
Petros Boufounos
89
Voted
CORR
2007
Springer
183views Education» more  CORR 2007»
14 years 9 months ago
Compressed Sensing and Redundant Dictionaries
This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, whic...
Holger Rauhut, Karin Schnass, Pierre Vandergheynst
ICASSP
2009
IEEE
15 years 4 months ago
CMOS compressed imaging by Random Convolution
We present a CMOS imager with built-in capability to perform Compressed Sensing coding by Random Convolution. It is achieved by a shift register set in a pseudo-random configurat...
Laurent Jacques, Pierre Vandergheynst, Alexandre B...
87
Voted
ICIP
2008
IEEE
15 years 3 months ago
Image representation by compressed sensing
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...
Bing Han, Feng Wu, Dapeng Wu