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Variational Denoising of Partly Textured Images by Spatially Varying Constraints
image denoising texture processing spatially varying fidelity term nonlinear diffusion variational image processing
2010/1/7
Denoising algorithms based on gradient dependent regularizers, such as nonlinear-diffusion processes and total variation denoising, modify images towards piecewise constant functions.
Although edge s...
Optimal Sparse Representation for Blind Deconvolution of Images
Optimal Sparse Representation Blind Deconvolution Images
2010/1/7
The relative Newton algorithm, previously proposed for quasi maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of ima...
Optimal Sparse Representation for Blind Deconvolution of Images
Optimal Sparse Representation Blind Deconvolution Images
2010/1/7
The relative Newton algorithm, previously proposed for quasi maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of ima...
Sparse ICA for Blind Separation of Transmitted and Reflected Images
transparent layers reflection polarization sparseness ICA blind source separation (BSS) wavelet packets clustering
2010/1/7
We address the problem of recovering a scene recorded through a semireflecting medium (i.e. planar lens), with a virtual reflected image being superimposed on the image of the scene transmitted throug...
Sparse ICA for Blind Separation of Transmitted and Reflected Images
transparent layers reflection polarization sparseness ICA blind source separation (BSS) wavelet packets clustering
2010/1/7
We address the problem of recovering a scene recorded through a semireflecting medium (i.e. planar lens), with a virtual reflected image being superimposed on the image of the scene transmitted throug...
Variational Blind Deconvolution of Multi-Channel Images
image restoration color images kernel estimation variational methods Non-linear PDEs
2010/1/7
The fundamental problem of denoising and deblurring images is addressed in this study. The great difficulty in this task is due to the ill-posedness of the problem. We analyze multi-channel images to ...
Variational Blind Deconvolution of Multi-Channel Images
image restoration color images kernel estimation variational methods Non-linear PDEs
2010/1/7
The fundamental problem of denoising and deblurring images is addressed in this study. The great difficulty in this task is due to the ill-posedness of the problem. We analyze multi-channel images to ...
Blind Deconvolution of Images Using Optimal Sparse Representations
Blind deconvolution quasi-maximum likelihood relative Newton optimization sparse representations
2010/1/7
The relative Newton algorithm, previously proposed for quasi-maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind
deconvolution of im...
Blind Deconvolution of Images Using Optimal Sparse Representations
Blind deconvolution quasi-maximum likelihood relative Newton optimization sparse representations
2010/1/7
The relative Newton algorithm, previously proposed for quasi-maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind
deconvolution of im...
Phase Unwrapping for 2-D Blind Deconvolution of Ultrasound Images
Phase unwrapping Poisson equation multiresolution
2010/1/6
In most approaches to the problem of two-dimensional
homomorphic deconvolution of ultrasound images, the estimation
of a corresponding point-spread function (PSF) is necessarily
the first stage in ...
Feature reduction for improved recognition of subcellular location patterns in fluorescence microscope images
proteomics subcellular location pattern subcellular location features
2009/12/23
The central goal of proteomics is to clarify the mechanism by which each protein in a given cell type carries out itsfunction. Automated protein subcellular location determination by fluorescence micr...
Towards a Systematics for Protein Subcellular Location: Quantitative Description of Protein Localization Patterns and Automated Analysis of Fluorescence Microscope Images
Automated Analysis Fluorescence Microscope Images
2009/12/22
Determination of the functions of all expressed proteins
represents one of the major upcoming challenges in
computational molecular biology. Since subcellular
location plays a crucial role in prote...
Automated analysis of patterns in fluorescencemicroscope images
Automated analysis of patterns fluorescencemicroscope images
2009/12/22
The widespread proliferation of
automated fluorescence-microscope
systems has made the acquisition of
digital images commonplace in
cell-biology research. This has created
a need for computer app...
Toward Objective Selection of Representative Microscope Images
Toward Objective Selection Representative Microscope Images
2009/12/22
Scientists wishing to communicate the essential characteristics of a pattern (such as an immunofluorescencedistribution) currently must make a subjective choice of one or two images to publish. We the...
Automated Recognition of Patterns Characteristic of Subcellular Structures in Fluorescence Microscopy Images
Patterns Characteristic Subcellular Structures Fluorescence
2009/12/22
Methods for numerical description and subsequent
classification of cellular protein localization
patterns are described. Images representing the
localization patterns of 4 proteins and DNA were
ob...