Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Applications of Shannon Information and Statistical Estimation Theory to Inverse Problems in Imaging

Not Accessible

Your library or personal account may give you access

Abstract

We apply statistical information and estimation theories to derive fundamental Bayesian bounds on image recovery from noisy data for two highly simplified imaging problems, namely single-pixel source localization and a two-pixel correlated image.

© 2011 Optical Society of America

PDF Article
More Like This
Statistical Performance Bounds for Coded-Aperture Compressive Spectral-Polarimetric Imaging

S. Prasad, Q. Zhang, R. Plemmons, and D. Brady
CTu3B.1 Computational Optical Sensing and Imaging (COSI) 2012

Angular Momentum, PSF Rotation, and 3D Source Localization: A Statistical Performance Analysis

S. Prasad, R. Kumar, and S. Narravula
CTh2C.1 Computational Optical Sensing and Imaging (COSI) 2014

An Information-Theoretic Analysis of Support-Assisted Optical Superresolution in One and Two Dimensions

Sudhakar Prasad and Xuan Luo
CTuC3 Computational Optical Sensing and Imaging (COSI) 2009

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2022 | Optica Publishing Group. All Rights Reserved