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Proceedings Paper

Multiple-object deconvolution (MODE) in support of imagery-based ATP classification of nonstationary TBM astronomical objects
Author(s): Aleksandr N. Safronov; Andrew A. Pahomov
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Paper Abstract

The aim of the present paper is to report preliminary results o : development of the image post-processing techniques, called Multiple Object DEconvolution (MODE) and Super Blind MODE (SBMODE), which are intended for joint restoration of the specified number of consec .tive distorted images of a highly-evolving unknown extended object being observed in the presence of unkno: 'n phase distortions (PSF). The solution to the problem is treated in the context of ir:oherent shift-invariant imaging and it is conceptually based on the generalized projecting onto convex ss (POCS), requiring only the qualitative knowledge (isoplanaticity, linearity, finiteness, positivity). Mathematically, the stated task is reduced to solving a class of inverse optical problems being described in form of a system of M (M 2) convolution-type Fredhoim integr ti equations containing a common unknown kernel (PSF). All the derived versions of the MODE are self-sufficient and Lhey do recover fairly reliably the blurred images for general compact objects in a relatively small numb. r of iterations. Brief theoretical analysis establishes uniqueness of a feasible solution and its close proxin iity to a true one under tolerance of poor (arbitrary) starting guesses. This versatile technique of few operators gives encouraging re e ults ,providing a basis for accurate imagebased ATP, target 3D-shaping and behavioural classification in n ax-real-time. The (SB)MODE technique is open to the imagery application ;in astronomy and defense plus biomedical imaging, including microscopies. Keywords: nonstationary space object; imaging telescope; imag sequence recovery; deconvolution; projection onto convex sets

Paper Details

Date Published: 7 June 1996
PDF: 16 pages
Proc. SPIE 2739, Acquisition, Tracking, and Pointing X, (7 June 1996); doi: 10.1117/12.241935
Show Author Affiliations
Aleksandr N. Safronov, Computing Ctr. Moscow/GASPROC (Russia)
Andrew A. Pahomov, Computing Ctr. Moscow/GASPROC (Russia)


Published in SPIE Proceedings Vol. 2739:
Acquisition, Tracking, and Pointing X
Michael K. Masten; Larry A. Stockum, Editor(s)

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