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Blind Image Deconvolution

Blind image deconvolution is constantly receiving increasing attention from the academic as well the industrial world due to both its;

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Partial Differential Equation Based Image Processing and Applications

. PDE based speckle reduction from images. Generalization to blind deconvolution problems. In this work, basic concepts of PDE based image;

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Bayesian Deconvolution of Sparse Processes

Bayesian Deconvolution of Sparse Processes: In this work, various Bayesian methods for deconvolution and blind deconvolution of sparse;

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Blind Equalizers By Techniques Of Optimal Non-Linear Filtering Theory

Blind deconvolution, fundamental in signal processing applications, is a challenging problem. Although blind equalization is essentially a;

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Adaptive Blind Signal And Image Processing

efficient algorithms for blind source separation, Independent, Principal, Minor Component Analysis, and Multichannel Blind Deconvolution (MBD) and;

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Deconvolution of Images and Spectra

Deconvolution is a technique in signal or image processing that is applied to recover information. When it is employed, it is usually;

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Signal Processing and Image Processing for Acoustical Imaging

- the 2D transform, fast Fourier transform (FFT) and applications, and deconvolution - before introducing readers to higher-order statistics;

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Unsupervised Adaptive Filtering

blind deconvolution and blind source separation Blind separation of independent sources based on multiuser kurtosis optimization criteria;

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Blind Source Separation

A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book;

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Advances in Imaging and Electron Physics

diversity Recent developments in the imaging of magnetic domains Explores stochastic deconvolution over groups ;

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Motion Deblurring

perspective, blind and non-blind approaches are discussed, including the use of single or multiple images; projective motion blur model; image priors;

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Approximate Deconvolution Models of Turbulence

the approximate solution of inverse problems. The resulting Approximate Deconvolution Models or ADMs have some advantages over more commonly;

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Blind

to their environment? The Blind might be the answer. Developed for naturalists by the Institute of Critical Zoologists, the Blind is a;

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Image Super-Resolution and Applications

: super-resolution with a priori information and blind super-resolution reconstruction of images. It also devotes chapters to the two;

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Image Super-Resolution and Applications

: super-resolution with a priori information and blind super-resolution reconstruction of images. It also devotes chapters to the two;

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Inverse Problems in Vision and 3D Tomography

methodology to examine inverse problems such as: noise removal; restoration by deconvolution; 2D or 3D reconstruction in X-ray, tomography or;

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Public Image Of Chemistry, The

Australia, this volume explores a blind spot in the science-society relationship and calls for a constructive dialog between scientists and their;

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Pressure Transient Formation and Well Testing

pretests, multiprobe and packer pressure transient tests, including derivative, convolution, and pressure-rate and pressure-pressure deconvolution;

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Tumor Immunology and Immunotherapy - Integrated Methods Part A

of this premier serial with quality chapters authored by leaders in the field. Specific chapters to this release include Deconvolution of the;

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Computing Brain Activity Maps from fMRI Time-Series Images

method works. The approaches include statistical parametric maps (SPM), hemodynamic response modeling and deconvolution, Bayesian, Fourier and;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2020

submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2020

in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2020

in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II;

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Bayesian Approach to Inverse Problems

address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2018

presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2018

presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the;

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