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

4 Scopus citations


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
Number of pages9
Editionp 2
ISBN (Print)081941638X
StatePublished - Dec 1 1994
EventVisual Communications and Image Processing '94 - Chicago, IL, USA
Duration: Sep 25 1994Sep 29 1994


OtherVisual Communications and Image Processing '94
CityChicago, IL, USA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics


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