Performance evaluation of image deconvolution techniques in space-variant astronomical imaging systems with nonlinearities

Karel Fliegel; Petr Janout; Jan Bednář; Lukáš Krasula; Stanislav Vítek; Jan Švihlík; Petr Páta

doi:10.1117/12.2187888

22 September 2015 Performance evaluation of image deconvolution techniques in space-variant astronomical imaging systems with nonlinearities

Karel Fliegel, Petr Janout, Jan Bednář, Lukáš Krasula, Stanislav Vítek, Jan Švihlík, Petr Páta

Author Affiliations +

Proceedings Volume 9599, Applications of Digital Image Processing XXXVIII; 959927 (2015) https://doi.org/10.1117/12.2187888
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

There are various deconvolution methods for suppression of blur in images. In this paper a survey of image deconvolution techniques is presented with focus on methods designed to handle images acquired with wide-field astronomical imaging systems. Image blur present in such images is space-variant especially due to space-variant point spread function (PSF) of the lens. The imaging system can contain also nonlinear electro-optical elements. Analysis of nonlinear and space-variant imaging systems is usually simplified so that the system is considered as linear and space-invariant (LSI) under specific constraints. Performance analysis of selected image deconvolution methods is presented in this paper, while considering space-variant nature of wide-field astronomical imaging system. Impact of nonlinearity on the overall performance of image deconvolution technique is also analyzed. Test images with characteristics obtained from the real system with space-variant wide-field input lens and nonlinear image intensifier are used for the performance analysis.

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Karel Fliegel, Petr Janout, Jan Bednář, Lukáš Krasula, Stanislav Vítek, Jan Švihlík, and Petr Páta "Performance evaluation of image deconvolution techniques in space-variant astronomical imaging systems with nonlinearities", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959927 (22 September 2015); https://doi.org/10.1117/12.2187888

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