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Inversion bayésienne myope et non-supervisée pour l'imagerie sur-résolue. Application à l'instrument SPIRE de l'observatoire spatial Herschel.

Abstract : The work involves data processing for super-resolution imaging with an application in astronomy. We are particularly interested in data from the SPIRE instrument of the spatial observatory Herschel of ESA, dedicated to far-infrared. The problems are mainly: the convolution of the spatial optical response, the sub-sampling and the presence of a thermal drift. The proposed approach is the inversion of data, ie taking into account the acquisition process as well as prior information to estimate the sky of interest. The first part of the work concerns the modelisation of the data acquisition process. The model consists of the mirror and feed-horns, the wavelength filter, the temperature sensitive sensor based on bolometers and scanning protocol. The obtained model, linear but not invariant due to sampling, is studied. Interesting properties, including perspective on data processing, are obtained especially in connection with the super-resolution capacity. The analysis also show useful properties for efficient algorithm. The second part of the work relies on a inference framework based on the usual Bayesian formalism. Since information is degraded, the inverse problem is ill-conditioned. The used method offers parameter estimation laws governing the balance between different information sources (hyper-parameters), in addition to the formalization of spatial regularity. Moreover, the proposed approach allows instrument parameters estimation and estimation of a slow thermal drift affecting all the sensor in conjunction with all the other parameters. All the information used to solve the problem is formalized through a posterior law. The estimator is chosen as the posterior mean calculated by means of an MCMC algorithm. An experimental study demonstrates the capacity of the approach to restore high spatial frequencies. The study also shows the potential of the approach for estimating hyper-parameters and instrument parameters.
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Contributor : François Orieux Connect in order to contact the contributor
Submitted on : Sunday, November 22, 2009 - 11:21:00 AM
Last modification on : Thursday, June 17, 2021 - 3:50:10 AM
Long-term archiving on: : Thursday, September 23, 2010 - 6:12:13 PM


  • HAL Id : tel-00433540, version 3




François Orieux. Inversion bayésienne myope et non-supervisée pour l'imagerie sur-résolue. Application à l'instrument SPIRE de l'observatoire spatial Herschel.. Traitement du signal et de l'image [eess.SP]. Université Paris Sud - Paris XI, 2009. Français. ⟨tel-00433540v3⟩



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