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Super-resolution images from blurred observations

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

In this paper, we present a technique for generating a high-resolution image from a blurred image sequence. The image sequence consists of decimated, blurred and noisy versions of the high-resolution image. The high-resolution image. The high-resolution resolution image is modeled as a Markov random field, and a maximum a posteriori estimation technique is used for image restoration. A fast algorithm based on Fast Fourier Transforms (FFTs) is derived to solve the resulting linear system. Numerical examples are given to illustrate the effectiveness of the method.

Original languageEnglish
Title of host publicationAdvanced Signal Processing Algorithms, Architectures, and Implementations XIII
Subtitle of host publicationOptical Science and Technology - SPIE's 48th Annual Meeting
EditorsFranklin T. Luk
PublisherSPIE
Pages328-335
Number of pages8
DOIs
Publication statusPublished - 24 Dec 2003
EventAdvanced Signal Processing Algorithms, Architectures, and Implementations XIII: Optical Science and Technology - SPIE's 48th Annual Meeting - San Diego, United States
Duration: 6 Aug 20038 Aug 2003

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Volume5205
ISSN (Print)0277-786X

Conference

ConferenceAdvanced Signal Processing Algorithms, Architectures, and Implementations XIII
Country/TerritoryUnited States
CitySan Diego
Period6/08/038/08/03

User-Defined Keywords

  • Circulant matrix
  • Fourier transform
  • High-resolution
  • Image reconstruction
  • Regularization

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