Paper
1 June 1994 Computer-aided solar astronomy: an image-processing example
Bertrand Collin, Veronique Serfaty, Bertrand Zavidovique
Author Affiliations +
Abstract
In this paper, we describe a complete pattern recognition procedure for extracting magnetic features in solar images, for tracking each feature from an image to another, thus deriving rotational and meridional motions with unequaled accuracy, and for tracking some of these features concurrently within a multispectral image flow, thus building the corresponding 3D magnetic structure and its evolution over time. The segmentation procedures lean upon the `translation' of the physical knowledge into an algorithmic functional decomposition. This methodology enables a fast and robust design of algorithms and leads to a higher accuracy. A multiresolution elastic matching is then used to track features and extract the surface motion of the sun. This matching implies designing an optimization scheme that fits the anisotropy of the motion as well as a target selection that requires no precomputed threshold. The multispectral images are segmented in a cooperative way, thus giving 3D structures. We introduce a fast algorithm to build the 3D connection between planar sections and show how the volumic information is necessary to tracking, based on the same elastic matching scheme.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bertrand Collin, Veronique Serfaty, and Bertrand Zavidovique "Computer-aided solar astronomy: an image-processing example", Proc. SPIE 2198, Instrumentation in Astronomy VIII, (1 June 1994); https://doi.org/10.1117/12.176822
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KEYWORDS
Magnetism

Image segmentation

Detection and tracking algorithms

Sun

3D image processing

Multispectral imaging

Image processing

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