Blind deconvolution algorithms for the restoration of atmospherically degraded imagery: a comparative analysis

Claudia S. Huebner; Mario Greco

doi:10.1117/12.800124

9 October 2008 Blind deconvolution algorithms for the restoration of atmospherically degraded imagery: a comparative analysis

Claudia S. Huebner, Mario Greco

Author Affiliations +

Proceedings Volume 7108, Optics in Atmospheric Propagation and Adaptive Systems XI; 71080M (2008) https://doi.org/10.1117/12.800124
Event: SPIE Remote Sensing, 2008, Cardiff, Wales, United Kingdom

Abstract

Suggestions from the field of image processing to compensate for turbulence effects and restore degraded images include motion-compensated image integration after which the image can be considered as a non-distorted image that has been blurred with a point spread function (PSF) the same size as the pixel motions due to the turbulence. Since this PSF is unknown, a blind deconvolution is still necessary to restore the image. By utilising different blind deconvolution algorithms along with the motion-compensated image integration, several variants of this turbulence compensation method are created. In this paper we discuss the differences of the various blind deconvolution algorithms employed and give a qualitative analysis of the turbulence compensation variants by comparing their respective restoration results. This is done by visual inspection as well as by means of different image quality metrics that analyse the high frequency components.

Citation Download Citation

Claudia S. Huebner and Mario Greco "Blind deconvolution algorithms for the restoration of atmospherically degraded imagery: a comparative analysis", Proc. SPIE 7108, Optics in Atmospheric Propagation and Adaptive Systems XI, 71080M (9 October 2008); https://doi.org/10.1117/12.800124

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