Super-exponential method for blur identification and image restoration

Thomas J. Kostas*, Laurent M. Mugnier, Aggelos K Katsaggelos, Alan Varteres Sahakian

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper examines a super-exponential method for blind deconvolution. Possibly non- minimal phase point spread functions (PSFs) are identified. The PSF is assumed to be low pass in nature. No other prior knowledge of the PSF or the original image is necessary to assure convergence of the algorithm. Results are shown using synthetically degraded satellite images in order to demonstrate the accuracy of the PSF estimates. In addition, radiographic images are restored with no knowledge of the PSF of the x-ray imaging system. These experiments suggest a promising application of this algorithm to a variety of blur identification problems.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages921-929
Number of pages9
Volume2308
Editionp 2
ISBN (Print)081941638X
StatePublished - Dec 1 1994
EventVisual Communications and Image Processing '94 - Chicago, IL, USA
Duration: Sep 25 1994Sep 29 1994

Other

OtherVisual Communications and Image Processing '94
CityChicago, IL, USA
Period9/25/949/29/94

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Kostas, T. J., Mugnier, L. M., Katsaggelos, A. K., & Sahakian, A. V. (1994). Super-exponential method for blur identification and image restoration. In Proceedings of SPIE - The International Society for Optical Engineering (p 2 ed., Vol. 2308, pp. 921-929). Society of Photo-Optical Instrumentation Engineers.