Possibilities Of Multichannel Blind Deconvolution In Solar Image Restoration

Statistics – Applications

Scientific paper

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Scientific paper

Blind image deconvolution as a tool for image restoration has been used in many applications. Astronomical images from the ground-based observation are degraded by seeing and by physical limitations of the real imaging system. Seeing is a degradation caused by the turbulence of the Earth's atmosphere and is the most difficult part to be modelled. Many mathematical models of the astronomical degradation have been proposed in the literature. Restoration algorithms try to invert these models and thus to estimate the original scene. In this paper, the framework of multichannel blind de-convolution (MBD) is used. The method assumes that for every ideal unobservable image several degraded observed images are available. We formulate the MBD as an energy-minimization problem with regularizations, which we solve by iterative alternate-minimization approach. Using of proper regularization terms yields good restoration results, as we demonstrate on the short exposure images of solar photosphere.

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