Blind image deconvolution using an evolutionary algorithm and image fusion

Salvador Gabarda; Gabriel Cristobal

doi:10.1117/12.608401

29 June 2005 Blind image deconvolution using an evolutionary algorithm and image fusion

Salvador Gabarda, Gabriel Cristobal

Proceedings Volume 5839, Bioengineered and Bioinspired Systems II; (2005) https://doi.org/10.1117/12.608401
Event: Microtechnologies for the New Millennium 2005, 2005, Sevilla, Spain

Abstract

This paper describes a new blind deconvolution method implemented by means of an evolutionary algorithm (EA), designed as a multi-objective optimization problem (MOP) approach. The last generation of the EA can be used for selecting the best image under a given quality criterion or submitted to a fusion method for producing an improved result. The fusion procedure is preferred here and implemented through a new robust method, based on the local space-frequency information extracted from the Wigner distribution of the image. This fusion method has been recently developed by the authors providing excellent experimental results.

Citation Download Citation

Salvador Gabarda and Gabriel Cristobal "Blind image deconvolution using an evolutionary algorithm and image fusion", Proc. SPIE 5839, Bioengineered and Bioinspired Systems II, (29 June 2005); https://doi.org/10.1117/12.608401

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