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Multiscale Astronomical Image Processing Based on Nonlinear Partial Differential Equations

Pesenson, Meyer and Roby, William and McCollum, Bruce (2008) Multiscale Astronomical Image Processing Based on Nonlinear Partial Differential Equations. Astrophysical Journal, 683 (1). pp. 566-576. ISSN 0004-637X. doi:10.1086/589276.

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Astronomical applications of recent advances in the field of nonastronomical image processing are presented. These innovative methods, applied to multiscale astronomical images, increase signal-to-noise ratio, do not smear point sources or extended diffuse structures, and are thus a highly useful preliminary step for detection of different features including point sources, smoothing of clumpy data, and removal of contaminants from background maps. We show how the new methods, combined with other algorithms of image processing, unveil fine diffuse structures while at the same time enhance detection of localized objects, thus facilitating interactive morphology studies and paving the way for the automated recognition and classification of different features. We have also developed a new application framework for astronomical image processing that implements some recent advances made in computer vision and modern image processing, along with original algorithms based on nonlinear partial differential equations. The framework enables the user to easily set up and customize an image-processing pipeline interactively; it has various common and new visualization features and provides access to many astronomy data archives. Altogether, the results presented here demonstrate the first implementation of a novel synergistic approach based on integration of image processing, image visualization, and image quality assessment.

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Additional Information:© 2008. The American Astronomical Society. Received 2007 December 4; accepted 2008 April 11; published 2008 August 10. Print publication: Issue 1 (2008 August 10). M.P. would like to thank George Helou, Alberto Noriega-Crespo, William Reach, Isaac Pesenson, Sean Carey, Inseok Song, Joe Chavez, Jim Ingalls, Tom Handley, Michael Egan, Achim Tappe, and Aniello Grado for helpful discussions. The authors would like to thank Loi Ly, Xiuqin Wu, Booth Hartley, and Tatiana Goldina for their contributions to the GUI. M.P. and B.M. thank Seppo Laine for helpful comments on an earlier draft of this paper. The authors would also like to thank the scientific editor for helpful comments and suggestions, and the anonymous referee for helpful suggestions. We would also like to thank the referee for bringing the paper of Chao & Tsai (2006) to our attention. M.P. would also like to thank Tetsuyasu Uekuma, Dina Pesenson, Igor Pesenson, and Liza Pesenson for discussions and support. This work is based on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. Facilities: Spitzer.
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Spitzer Space TelescopeUNSPECIFIED
Subject Keywords:astrometry; diffusion; methods: data analysis; methods: numerical; techniques: image processing
Issue or Number:1
Record Number:CaltechAUTHORS:PESapj08
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:12982
Deposited By: Archive Administrator
Deposited On:14 Jan 2009 20:50
Last Modified:08 Nov 2021 22:34

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