An iterative SNR estimation algorithm for wiener deconvolution of self-similar images distorted by camera shake blurring

Authors:
A. Pereyra Marcelo;Jacoby Daniel
Affiliations:
Applied Digital Electronics Group, Instituto Tecnológico de Buenos Aires, Argentina;Applied Digital Electronics Group, Instituto Tecnológico de Buenos Aires, Argentina
Venue:
SSIP'08 Proceedings of the 8th conference on Signal, Speech and image processing
Year:
2008

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Abstract

The Wiener deconvolution technique can successfully restore real world images distorted by camera shake blurring. However, its performance is highly sensitive to the estimated SNR, a parameter that is hard to estimate correctly a priori. An iterative algorithm is proposed to find a suitable SNR by gradually testing the Wiener deconvolution on a fragment of the blurred image and observing the self-symmetry of the result, a quality measure that can be estimated by comparing the vertical and horizontal gradient distributions.