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» On Sparsity and Overcompleteness in Image Models
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CVPR
2012
IEEE
11 years 11 months ago
Compressive depth map acquisition using a single photon-counting detector: Parametric signal processing meets sparsity
Active range acquisition systems such as light detection and ranging (LIDAR) and time-of-flight (TOF) cameras achieve high depth resolution but suffer from poor spatial resolutio...
Andrea Colaco, Ahmed Kirmani, Gregory A. Howland, ...
CORR
2010
Springer
167views Education» more  CORR 2010»
13 years 9 months ago
Network Flow Algorithms for Structured Sparsity
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...
ICIP
2005
IEEE
14 years 10 months ago
Signal estimation using multiple-wavelet representations and Gaussian models
Signal processing using over-complete representations has been an active research field in recent years. In this article, we study the following two related problems: (1) given tw...
Guang Deng
ICASSP
2008
IEEE
14 years 3 months ago
Image inpainting with a wavelet domain Hidden Markov tree model
We present a novel technique for image inpainting, the problem of filling-in missing image parts. Image inpainting is ill-posed and we adopt a probabilistic model-based approach ...
George Papandreou, Petros Maragos, Anil Kokaram
ICIP
2007
IEEE
14 years 10 months ago
Statistically Driven Sparse Image Approximation
Finding the sparsest approximation of an image as a sum of basis functions drawn from a redundant dictionary is an NPhard problem. In the case of a dictionary whose elements form ...
Rosa M. Figueras i Ventura, Eero P. Simoncelli