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» Sampling and Reconstruction of Operators
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TSP
2008
116views more  TSP 2008»
13 years 5 months ago
Nonideal Sampling and Regularization Theory
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, wh...
Sathish Ramani, Dimitri Van De Ville, Thierry Blu,...
TOG
2008
140views more  TOG 2008»
13 years 5 months ago
Multidimensional adaptive sampling and reconstruction for ray tracing
We present a new adaptive sampling strategy for ray tracing. Our technique is specifically designed to handle multidimensional sample domains, and it is well suited for efficientl...
Toshiya Hachisuka, Wojciech Jarosz, Richard Peter ...
ICIP
2005
IEEE
14 years 7 months ago
Sampling in practice: is the best reconstruction space bandlimited?
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant " space, ...
Sathish Ramani, Dimitri Van De Ville, Michael Unse...
TSP
2010
12 years 12 months ago
Distributed sampling of signals linked by sparse filtering: theory and applications
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
TMI
2011
127views more  TMI 2011»
13 years 6 days ago
Reconstruction of Large, Irregularly Sampled Multidimensional Images. A Tensor-Based Approach
Abstract—Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this prob...
Oleksii Vyacheslav Morozov, Michael Unser, Patrick...