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» Complexity-Regularized Image Denoising
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ICASSP
2011
IEEE
14 years 9 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
16 years 20 days 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
16 years 7 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»
15 years 12 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
16 years 7 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...