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Open AccessJournal ArticleDOI

A New Poisson Noise Filter Based on Weights Optimization

TLDR
In this article, the authors proposed a new image denoising algorithm when the data is contaminated by a Poisson noise, which is based on a weighted linear combination of the observed image.
Abstract
We propose a new image denoising algorithm when the data is contaminated by a Poisson noise As in the Non-Local Means filter, the proposed algorithm is based on a weighted linear combination of the observed image But in contrast to the latter where the weights are defined by a Gaussian kernel, we propose to choose them in an optimal way First some "oracle" weights are defined by minimizing a very tight upper bound of the Mean Square Error For a practical application the weights are estimated from the observed image We prove that the proposed filter converges at the usual optimal rate to the true image Simulation results are presented to compare the performance of the presented filter with conventional filtering methods

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Citations
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Journal ArticleDOI

A Guided Tour of Selected Image Processing and Analysis Methods for Fluorescence and Electron Microscopy

TL;DR: Recent advances in fluorescence and electron microscopy are presented and dedicated image processing and analysis methods required to quantify phenotypes for a limited number but typical studies in cell imaging are presented.
Journal ArticleDOI

Delay dynamic double integral inequalities on time scales with applications

TL;DR: In this article, the explicit bounds for three generalized delay dynamic Gronwall-Bellman type integral inequalities on time scales are presented, which are the unification of continuous and discrete results, as applications, the boundedness for the solutions of delay dynamic integro-differential equations with initial conditions is discussed.
Journal ArticleDOI

Survey on mixed impulse and Gaussian denoising filters

TL;DR: A comprehensive survey on mixed impulse and Gaussian denoising filters which are applied to an image in order to gauge the effects of this type of noise combination and to then determine optimal ways that can overcome such effects is presented in this paper.
Journal ArticleDOI

Poisson image denoising by piecewise principal component analysis and its application in single-particle X-ray diffraction imaging

TL;DR: It is shown that the resolution of three-dimensional reconstruction from XFEL diffraction images is improved when the data are preprocessed with PWPCA, and the first application of such approaches to single-particle X-ray free-electron laser (XFEL) data is shown.
References
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Journal ArticleDOI

$rm K$ -SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

TL;DR: A novel algorithm for adapting dictionaries in order to achieve sparse signal representations, the K-SVD algorithm, an iterative method that alternates between sparse coding of the examples based on the current dictionary and a process of updating the dictionary atoms to better fit the data.
Journal ArticleDOI

A Review of Image Denoising Algorithms, with a New One

TL;DR: A general mathematical and experimental methodology to compare and classify classical image denoising algorithms and a nonlocal means (NL-means) algorithm addressing the preservation of structure in a digital image are defined.
Book

Local polynomial modelling and its applications

TL;DR: Applications of Local Polynomial Modeling in Nonlinear Time Series and Automatic Determination of Model Complexity and Framework for Local polynomial regression.
Journal ArticleDOI

Image denoising using scale mixtures of Gaussians in the wavelet domain

TL;DR: The performance of this method for removing noise from digital images substantially surpasses that of previously published methods, both visually and in terms of mean squared error.
Journal ArticleDOI

Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems

TL;DR: A fast algorithm is derived for the constrained TV-based image deblurring problem with box constraints by combining an acceleration of the well known dual approach to the denoising problem with a novel monotone version of a fast iterative shrinkage/thresholding algorithm (FISTA).
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