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114
Voted
CVPR
2008
IEEE
16 years 2 months ago
An efficient algorithm for compressed MR imaging using total variation and wavelets
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
116
Voted
ICIP
2009
IEEE
15 years 7 months ago
A Novel Framework for Imaging Using Compressed Sensing
Recently, there has been growing interest in using compressed sensing to perform imaging. Most of these algorithms capture the image of a scene by taking projections of the imaged ...
Pradeep Sen and Soheil Darabi
104
Voted
LCTRTS
2005
Springer
15 years 6 months ago
A dictionary construction technique for code compression systems with echo instructions
Dictionary compression mechanisms identify redundant sequences of instructions that occur in a program. The sequences are extracted and copied to a dictionary. Each sequence is th...
Philip Brisk, Jamie Macbeth, Ani Nahapetian, Majid...
97
Voted
CSR
2006
Springer
15 years 4 months ago
Window Subsequence Problems for Compressed Texts
Given two strings (a text t of length n and a pattern p) and a natural number w, window subsequence problems consist in deciding whether p occurs as a subsequence of t and/or findi...
Patrick Cégielski, Irène Guessarian,...
87
Voted
CORR
2010
Springer
128views Education» more  CORR 2010»
15 years 27 days ago
Blind Compressed Sensing
The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measuremen...
Sivan Gleichman, Yonina C. Eldar