Sciweavers

Share
CORR
2010
Springer
145views Education» more  CORR 2010»
8 years 7 months ago
Orthogonal symmetric Toeplitz matrices for compressed sensing: Statistical isometry property
Recently, the statistical restricted isometry property (RIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this paper...
Kezhi Li, Lu Gan, Cong Ling
ICIP
2009
IEEE
8 years 8 months ago
Informative sensing of natural images
The theory of compressed sensing tells a dramatic story that sparse signals can be reconstructed near-perfectly from a small number of random measurements. However, recent work ha...
Hyun Sung Chang, Yair Weiss, William T. Freeman
ICIP
2009
IEEE
8 years 8 months ago
Randomness-in-Structured Ensembles for compressed sensing of images
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Abdolreza A. Moghadam, Hayder Radha
PERCOM
2010
ACM
8 years 8 months ago
Resilient image sensor networks in lossy channels using compressed sensing
—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received i...
Scott Pudlewski, Arvind Prasanna, Tommaso Melodia
ICMCS
2010
IEEE
191views Multimedia» more  ICMCS 2010»
8 years 8 months ago
Disparity-compensated compressed-sensing reconstruction for multiview images
In a multiview-imaging setting, image-acquisition costs could be substantially diminished if some of the cameras operate at a reduced quality. Compressed sensing is proposed to ef...
Maria Trocan, Thomas Maugey, James E. Fowler, B&ea...
FOCM
2010
82views more  FOCM 2010»
8 years 8 months ago
Stability and Instance Optimality for Gaussian Measurements in Compressed Sensing
In compressed sensing we seek to gain information about vector x ∈ RN from d << N nonadaptive linear measurements. Candes, Donoho, Tao et. al. ( see e.g. [2, 4, 8]) propos...
P. Wojtaszczyk
CORR
2010
Springer
171views Education» more  CORR 2010»
8 years 8 months ago
Graphical Models Concepts in Compressed Sensing
This paper surveys recent work in applying ideas from graphical models and message passing algorithms to solve large scale regularized regression problems. In particular, the focu...
Andrea Montanari
JC
2007
119views more  JC 2007»
8 years 10 months ago
Deterministic constructions of compressed sensing matrices
Compressed sensing is a new area of signal processing. Its goal is to minimize the number of samples that need to be taken from a signal for faithful reconstruction. The performan...
Ronald A. DeVore
CORR
2007
Springer
183views Education» more  CORR 2007»
8 years 10 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
CORR
2010
Springer
249views Education» more  CORR 2010»
8 years 10 months ago
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Blake Hunter, Thomas Strohmer
books