Non-parametric PSF estimation from celestial transit solar images using blind deconvolution

摘要: Context : Characterization of instrumental effects in astronomical imaging is important order to extract accurate physical information from the observations. The measured image a real optical instrument usually represented by convolution an ideal with Point Spread Function (PSF). Additionally, acquisition process also contaminated other sources noise (read-out, photon-counting). problem estimating both PSF and denoised called blind deconvolution ill-posed. Aims We propose scheme that relies on regularization. Contrarily most methods presented literature, our method does not assume parametric model can thus be applied any telescope. Methods Our uses wavelet analysis prior weak assumptions PSF. use observations celestial transit, where occulting body assumed black disk. These constraints allow us retain meaningful solutions for filter image, eliminating trivial, translated, interchanged solutions. Under additive Gaussian assumption, they enforce canceling avoid reconstruction artifacts promoting whiteness residual between blurred cleaned data. Results synthetic experimental estimated SECCHI/EUVI using 2007 Lunar SDO/AIA 2012 Venus transit. show proposed non-parametric able estimate core similar quality literature. that, if these estimations are incorporated model, resulting outperforms methods.