Publication details

Probabilistic suppression of astronomical degradations


Haindl Michal, Šimberová Stanislava

serial: Proceedings of Abstracts of Modern Solar Facilities - Advanced Solar Science, p. 1-1

action: Modern solar facilities - advanced solar science, (Göttingen, DE, 27.09.2006-29.09.2006)

research: CEZ:AV0Z10750506

project(s): 1ET400750407, GA AV ČR, 1M0572, GA MŠk, GA102/04/0155, GA ČR, 2C06019, MŠk

keywords: image restoration, multichannel restoration

abstract (eng):

A multichannel fast adaptive recursive restoration method based on the underlying spatial probabilistic image model is presented. The method assumes linear degradation model with the unknown possibly non-homogeneous point-spread function and additive noise for each of mutually registered degraded observations. Pixels in the vicinity of image steep discontinuities are left unrestored to minimize restoration blurring effect. The method is completely autonomous and doesn't assume any knowledge of the underlying degradation process. The algorithm is verified on the artificial data with known ideal image. In the multichannel input are blurred channels created from the ideal image using various degradation functions. Then the method is applied to the real optical solar data. The experiments are carried on the synthetic data set and on a sequence of the short-exposure solar photosphere images. The multichannel input is presented by the temporal plains of a data cube. The results are compared under the most frequented criterions of image quality. The method can be also easily and naturally generalized for multispectral (e.g. colour, multispectral satellite images) or registered images which is seldom the case for alternative methods.

abstract (cze):

Viz. anglický abstrakt.

Cosati: 09K