Smoothing of astronomical images with Poisson distribution

Zuzana Krbcová; Jaromír Kukal; Jan Švihlík; Karel Fliegel

doi:10.1117/12.2274121

19 September 2017 Smoothing of astronomical images with Poisson distribution

Zuzana Krbcová, Jaromír Kukal, Jan Švihlík, Karel Fliegel

Proceedings Volume 10396, Applications of Digital Image Processing XL; 103962V (2017) https://doi.org/10.1117/12.2274121
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

Images obtained from an astronomical digital camera are of integer nature as event counters in every pixel of its image sensor. The quality of the captured images is in uenced mostly by the camera characteristics and photon noise caused by natural random uctuation of observed light. We suppose the image pixel intensity as a mean value of the signal with Poisson distribution. The application of maximum likelihood method with image gradient regularization leads to variational task in discrete formulation. This variational task has only one unique solution on which the novel numerical method of image smoothing is based. The performance of the proposed smoothing procedure is tested using real images obtained from the digital camera in Meteor Automatic Imager and Analyzer (MAIA).

Citation Download Citation

Zuzana Krbcová, Jaromír Kukal, Jan Švihlík, and Karel Fliegel "Smoothing of astronomical images with Poisson distribution", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103962V (19 September 2017); https://doi.org/10.1117/12.2274121

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