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Journal ArticleDOI

Bayesian-Based Iterative Method of Image Restoration

TLDR
An iterative method of restoring degraded images was developed by treating images, point spread functions, and degraded images as probability-frequency functions and by applying Bayes’s theorem.
Abstract
An iterative method of restoring degraded images was developed by treating images, point spread functions, and degraded images as probability-frequency functions and by applying Bayes’s theorem. The method functions effectively in the presence of noise and is adaptable to computer operation.

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Journal ArticleDOI

Deep-Learning-Based Image Reconstruction and Enhancement in Optical Microscopy

TL;DR: An overview of some of the recent work using deep neural networks to advance computational microscopy and sensing systems, also covering their current and future biomedical applications.
Journal ArticleDOI

Wide field-of-view lens-free fluorescent imaging on a chip

TL;DR: An on-chip fluorescent detection platform that can simultaneously image fluorescent micro-objects or labeled cells over an ultra-large field-of-view of 2.5 cm x 3.5cm without the use of any lenses, thin-film filters and mechanical scanners is demonstrated.
Journal ArticleDOI

Bayesian deconvolution I: Convergent properties

TL;DR: In this article, an iterative procedure to achieve spectral deconvolution by application of Bayes' postulate is presented, and an analytical treatment for a Gaussian response function is used to indicate how the resolution attained depends upon the number of iterations.
Journal ArticleDOI

Studies of jet mass in dijet and W/Z + jet events

S. Chatrchyan, +2277 more
TL;DR: In this article, a mass spectra for jets reconstructed using the anti-kt and Cambridge-Aachen algorithms is studied for different jet grooming techniques in data corresponding to an integrated luminosity of 5 inverse femtobarns, recorded with the CMS detector in proton-proton collisions at the LHC at a center-of-mass energy of 7 TeV.
References
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Book

Modern probability theory and its applications

TL;DR: Probability Theory as the study of Mathematical Models of Random Phenomena as mentioned in this paper is a generalization of probability theory for the study and analysis of statistical models of random variables.
Journal ArticleDOI

Image Evaluation and Restoration

TL;DR: The extent to which the processing approaches the optimum can be evaluated by determining the fraction of the total information content of the image which can be visually extracted after processing.
Journal ArticleDOI

Restoration of Turbulence-Degraded Images*

TL;DR: In this paper, the amplitude and phase coefficients of the two-dimensional Fourier series representing the degraded images were corrected by applying corrections to the optical transfer function of the turbulence measured at the time the images were photographed.
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