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149
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TIP
2010
127views more  TIP 2010»
15 years 27 days ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
156
Voted
TIT
2010
174views Education» more  TIT 2010»
14 years 9 months ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
SSD
2007
Springer
133views Database» more  SSD 2007»
15 years 8 months ago
Compression of Digital Road Networks
Abstract. In the consumer market, there has been an increasing interest in portable navigation systems in the last few years. These systems usually work on digital map databases st...
Jonghyun Suh, Sungwon Jung, Martin Pfeifle, Khoa T...
117
Voted
SMI
2003
IEEE
138views Image Analysis» more  SMI 2003»
15 years 7 months ago
Higher Order Prediction for Geometry Compression
A lot of techniques have been developed for the encoding of triangular meshes as this is a widely used representation for the description of surface models. Although methods for t...
Stefan Gumhold, Rachida Amjoun
121
Voted
TCSV
2002
161views more  TCSV 2002»
15 years 2 months ago
Blocking artifact detection and reduction in compressed data
A novel frequency-domain technique for image blocking artifact detection and reduction is presented in this paper. The algorithm first detects the regions of the image which presen...
George A. Triantafyllidis, Dimitrios Tzovaras, Mic...