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SIAMSC
2010
141views more  SIAMSC 2010»
13 years 6 months ago
An Iterative Method for Edge-Preserving MAP Estimation When Data-Noise Is Poisson
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
Johnathan M. Bardsley, John Goldes
ECCV
2006
Springer
14 years 9 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
MICCAI
2008
Springer
14 years 8 months ago
A Novel Explicit 2D+t Cyclic Shape Model Applied to Echocardiography
In this paper, we propose a novel explicit 2D+t cyclic shape model that extends the Point Distribution Model (PDM) to shapes like myocardial contours with cyclic dynamics. We also ...
Ramón Casero, J. Alison Noble
CORR
2010
Springer
172views Education» more  CORR 2010»
13 years 7 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang
PAMI
2008
198views more  PAMI 2008»
13 years 7 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation....
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...