Joint maximum a posteriori estimation of object and PSF for turbulence-degraded images

The performance of high resolution imaging with large optical instruments is severely limited by the atmospheric turbulence. Adaptive optics offers a real time compensation of the turbulence. The correction is however only partial and the long exposure images must be deconvolved to restore the fine details of the object. The aim of this communication js to further study and validate on AO images a recently proposed "myopic" deconvolution scheme. This approach takes into account the noise in the image, the imprecise knowledge of the PSF, and the available a priori information on the object to be restored as well as on the PSF. The PSF is characterized by its ensemble mean and power spectral density which can be derived from the turbulence statistics. Various object priors are tested (quadratic and L norm regularization). The myopic deconvolution is first compared, on a simulated astronomical extended source, to classical deconvolution. It is shown to improve the object restoration particularly in the case poor PSF estimations due to rapidly evolving turbulence conditions. The myopic deconvolution is then applied on the experimental image of a triple star. A good astrometric and photometric precision is obtained, especially when using a multiple star model for the object. Keywords: adaptive optics, atmospheric turbulence, deconvolution, image restoration, inverse problems, telescope

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