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.read more
Citations
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Posted ContentDOI
BigStitcher: Reconstructing high-resolution image datasets of cleared and expanded samples
David Hörl,David Hörl,Fabio Rojas Rusak,Friedrich Preusser,Paul W. Tillberg,Nadine Randel,Nadine Randel,Raghav K. Chhetri,Albert Cardona,Albert Cardona,Philipp J. Keller,Hartmann Harz,Heinrich Leonhardt,Mathias Treier,Mathias Treier,Stephan Preibisch +15 more
TL;DR: The BigStitcher software is developed that efficiently handles and reconstructs large multi-tile, multi-view acquisitions compensating all major optical effects, thereby making single-cell resolved whole-organ datasets amenable to biological studies.
Journal ArticleDOI
Tumor quantification in clinical positron emission tomography.
TL;DR: The current status of tumor quantification methods and their applications to clinical oncology are reviewed, and factors that impede quantitative assessment and limit its accuracy and reproducibility are summarized.
Journal ArticleDOI
Returning magnetic flux in sunspot penumbrae
B. Ruiz Cobo,A. Asensio Ramos +1 more
TL;DR: In this article, a principal component decomposition of the Stokes profiles was inverted to infer the magnetic field in the penumbra using SIR, and the reversed polarity fields at the bord er of many bright penumbral filaments were detected.
Journal ArticleDOI
Rapid image deconvolution and multiview fusion for optical microscopy.
Min Guo,Yue Li,Yijun Su,Talley J. Lambert,Damian Dalle Nogare,Mark W. Moyle,Leighton H. Duncan,Richard Ikegami,Anthony Santella,Ivan Rey-Suarez,Ivan Rey-Suarez,Daniel S. Green,Anastasia Beiriger,Jiji Chen,Harshad D. Vishwasrao,Sundar Ganesan,Victoria E. Prince,Jennifer C. Waters,Christina M. Annunziata,Markus Hafner,William A. Mohler,Ajay B. Chitnis,Arpita Upadhyaya,Ted B. Usdin,Zhirong Bao,Daniel A. Colón-Ramos,Daniel A. Colón-Ramos,Daniel A. Colón-Ramos,Patrick J. La Riviere,Patrick J. La Riviere,Huafeng Liu,Yicong Wu,Hari Shroff,Hari Shroff +33 more
TL;DR: Advances in algorithm and software design result in image processing times that are tenfold to several thousand fold faster than with previous methods, and microscopy datasets are processed orders-of-magnitude faster with improved algorithms and deep learning.
Journal ArticleDOI
Cascades of Regression Tree Fields for Image Restoration
TL;DR: A cascade model for image restoration that consists of a Gaussian CRF at each stage that is semi-parametric, i.e., it depends on the instance-specific parameters of the restoration problem, such as the blur kernel.
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.