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» An Overview Of Inverse Problem Regularization Using Sparsity
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ICIP
2002
IEEE
14 years 8 months ago
Complexity regularized shape estimation from noisy Fourier data
We consider the estimation of an unknown arbitrary 2D object shape from sparse noisy samples of its Fourier transform. The estimate of the closed boundarycurve is parametrized by ...
Natalia A. Schmid, Yoram Bresler, Pierre Moulin
ICIP
2009
IEEE
13 years 4 months ago
Joint deconvolution and demosaicing
We present a new method to jointly perform deblurring and colordemosaicing of RGB images. Our method is derived following an inverse problem approach in a MAP framework. To avoid ...
Ferréol Soulez, Eric Thiébaut
ECCV
2006
Springer
13 years 10 months ago
Consistent and Elastic Registration of Histological Sections Using Vector-Spline Regularization
Here we present a new image registration algorithm for the alignment of histological sections that combines the ideas of B-spline based elastic registration and consistent image re...
Ignacio Arganda-Carreras, Carlos Oscar Sánc...
UAI
2008
13 years 8 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
ICASSP
2010
IEEE
13 years 4 months ago
Psychoacoustically motivated, frequency dependent Tikhonov regularization for soundfield parametrization
Noise is inevitably introduced during model based parametrization of acoustic fields, acquired using microphone arrays. This is due to the finite number of microphones used, the f...
Deep Sen, Shuai Wang, Andy Deffrasnes