Spatially adaptive image restoration for autoradiography

John A. Goyette*, Moon G. Kang, Aggelos K. Katsaggelos, Gregory D. Lapin

*Corresponding author for this work

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

6 Scopus citations


In this paper, we present a model that is used to improve the resolution of autoradiographic images. The model involves a point spread function (PSF) due to the radiated pattern of emitted photons combined with a signal-dependent noise source due to the granularity of x-ray recording film. A theoretical expression for the PSF is presented, and experimental measurements are performed using 51Cr microspheres. An iterative regularized image restoration algorithm is developed using a weighting matrix to incorporate the signal-dependent nature of the noise. Since information about the original undegraded image is not completely available, we make use of a regularization functional that is updated at each iteration to optimize the solution process. Our experimental results indicate that the resolution of autoradiographic images is improved by 43% using this algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Number of pages12
ISBN (Print)0819419869, 9780819419866
StatePublished - 1995
EventOptical Engineering Midwest'95. Part 2 (of 2) - Chicago, IL, USA
Duration: May 18 1995May 19 1995


OtherOptical Engineering Midwest'95. Part 2 (of 2)
CityChicago, IL, USA

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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