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» Complexity-Regularized Image Denoising
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ICASSP
2011
IEEE
12 years 11 months ago
Dual constrained TV-based regularization
Algorithms based on the minimization of the Total Variation are prevalent in computer vision. They are used in a variety of applications such as image denoising, compressive sensi...
Camille Couprie, Hugues Talbot, Jean-Christophe Pe...
ISBI
2009
IEEE
14 years 2 months ago
A Compressed Sensing Approach for Biological Microscopic Image Processing
In fluorescence microscopy the noise level and the photobleaching are cross-dependent problems since reducing exposure time to reduce photobleaching degrades image quality while ...
Marcio de Moraes Marim, Elsa D. Angelini, Jean-Chr...
ICIP
2009
IEEE
14 years 8 months ago
Weighted Average Denoising With Sparse Orthonormal Transforms
Sparse Orthonormal Transforms (SOT) has recently been proposed as a data compression method that can achieve sparser representations in transform domain. Given initial conditions,...
SMI
2006
IEEE
147views Image Analysis» more  SMI 2006»
14 years 1 months ago
Smoothing by Example: Mesh Denoising by Averaging with Similarity-Based Weights
In this paper, we propose a new and powerful shape denoising technique for processing surfaces approximated by triangle meshes and soups. Our approach is inspired by recent non-lo...
Shin Yoshizawa, Alexander G. Belyaev, Hans-Peter S...
ICPR
2008
IEEE
14 years 8 months ago
An adaptive Monte Carlo approach to nonlinear image denoising
This paper introduces a novel stochastic approach to image denoising using an adaptive Monte Carlo scheme. Random samples are generated from the image field using a spatially-adap...
Alexander Wong, Akshaya Kumar Mishra, Paul W. Fieg...