Bayesian image deblurring and boundary effects

Daniela Calvetti; Erkki Somersalo

doi:10.1117/12.623160

16 September 2005 Bayesian image deblurring and boundary effects

Daniela Calvetti, Erkki Somersalo

Proceedings Volume 5910, Advanced Signal Processing Algorithms, Architectures, and Implementations XV; 59100X (2005) https://doi.org/10.1117/12.623160
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

We consider the deconvolution problem of estimating an image from a noisy blurred version of it. In particular, we are interested in the boundary effects: since the convolution operator is non-local, the blurred image depend on the scenery outside the field of view. Ignoring this dependency leads to image distortion known as boundary effect. In this article, we consider two different approaches to treat the non-locality. One is to estimate the image extended outside the field of view. The other is to treat the influence of the out of view scenery as boundary clutter. both approaches are considered from the Bayesian point of view.

Citation Download Citation

Daniela Calvetti and Erkki Somersalo "Bayesian image deblurring and boundary effects", Proc. SPIE 5910, Advanced Signal Processing Algorithms, Architectures, and Implementations XV, 59100X (16 September 2005); https://doi.org/10.1117/12.623160

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