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ICIP
2002
IEEE
14 years 9 months ago
Satellite and aerial image deconvolution using an EM method with complex wavelets
In this paper, we present a new deconvolution method, able to deal with noninvertible blurring functions. To avoid noise amplification, a prior model of the image to be reconstruc...
André Jalobeanu, Josiane Zerubia, Má...
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 9 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
TSP
2010
13 years 2 months ago
Joint detection and estimation of multiple objects from image observations
The problem of jointly detecting multiple objects and estimating their states from image observations is formulated in a Bayesian framework by modeling the collection of states as ...
Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Sute...
VISAPP
2007
13 years 9 months ago
Image deconvolution using a stochastic differential equation approach
We consider the problem of image deconvolution. We foccus on a Bayesian approach which consists of maximizing an energy obtained by a Markov Random Field modeling. MRFs are classi...
Xavier Descombes, M. Lebellego, Elena Zhizhina
IDA
2009
Springer
14 years 9 days ago
Image Source Separation Using Color Channel Dependencies
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
Koray Kayabol, Ercan E. Kuruoglu, Bülent Sank...