Bayesian-Based Iterative Method of Image Restoration*
Journal of the Optical Society of AmericaPublished 1 January 1972
William Hadley Richardson
Citations4,144
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
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.
Keywords
Computer ScienceEngineering
Journal of the Royal Statistical Society Series A (General)Modern Probability Theory and its Applications.
769 Citations1961D. M. G. Wishart, Emanuel Parzen
Journal of the Optical Society of AmericaImage Evaluation and Restoration*†
150 Citations1966James L. Harris
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 of the Optical Society of AmericaRestoration of Turbulence-Degraded Images*
148 Citations1967B. L. McGlamery
Journal of the Franklin InstituteRecent developments in information and decision processes
82 Citations1963
