Computational aspects of regularized image reconstruction

John B. Abbiss; Bryan J. Brames; Michael A. Fiddy

doi:10.1117/12.23622

1 November 1990 Computational aspects of regularized image reconstruction

John B. Abbiss, Bryan J. Brames, Michael A. Fiddy

Proceedings Volume 1351, Digital Image Synthesis and Inverse Optics; (1990) https://doi.org/10.1117/12.23622
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States

Abstract

Image restoration procedures are commonly unstable in the presence of noise, and some technique for restoring stability becomes essential. The methods of regularization theory are particularly appropriate for this purpose. A specific type of regularized solution is introduced in the general context of image reconstruction. A super-resolution problem is then considered from the point of view of the computational tasks involved, with particular reference to the estimation of certain key parameters and to implementations which increase the efficiency of the calculations. Parameter estimation is performed by weighted cross-validation. The improvement in efficiency is achieved through the exploitation of symmetries or cyclic properties inherent in the reconstruction operator. The concept of displacement rank is introduced and estimates made of the computational burden associated with various classes of regularized reconstruction matrices.

Citation Download Citation

John B. Abbiss, Bryan J. Brames, and Michael A. Fiddy "Computational aspects of regularized image reconstruction", Proc. SPIE 1351, Digital Image Synthesis and Inverse Optics, (1 November 1990); https://doi.org/10.1117/12.23622

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