Signal-to-noise ratio and bias of various deconvolution from wavefront sensing estimators

Jean-Marc Conan; Vincent Michau; Gerard Rousset

doi:10.1117/12.254206

14 October 1996 Signal-to-noise ratio and bias of various deconvolution from wavefront sensing estimators

Jean-Marc Conan, Vincent Michau, Gerard Rousset

Proceedings Volume 2828, Image Propagation through the Atmosphere; (1996) https://doi.org/10.1117/12.254206
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

Deconvolution from wavefront sensing is a powerful and relatively low cost high resolution imaging technique compensating for the degradation due to atmospheric turbulence. It is based on a simultaneous recording of short exposure images and wavefront sensing data. Two different deconvolution schemes have been proposed: the self- referenced estimator originally presented by Primot et al. and the post-referenced estimator recently suggested by Roggemann et al. A theoretical study allows us to estimate the bias and signal to noise ratio of these various estimators. Self-referenced deconvolution is shown to have a good signal-to-noise ratio but the estimator is biased, while post-referenced deconvolution is bias-free but has very limited performance for bright sources. A new-self referenced deconvolution scheme accounting for the wavefront sensing noise is proposed. This leads to an optimal data reduction which should overcome the bias problems while providing good signal-to-noise ratio performances. Encouraging numerical results are presented.

Citation Download Citation

Jean-Marc Conan, Vincent Michau, and Gerard Rousset "Signal-to-noise ratio and bias of various deconvolution from wavefront sensing estimators", Proc. SPIE 2828, Image Propagation through the Atmosphere, (14 October 1996); https://doi.org/10.1117/12.254206

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