Automated Spatiotemporal Analysis of Fibrils and Coronal Rain Using the Rolling Hough Transform

• Published in: Solar physics Vol. 292; no. 9; p. 1
• Main Author: Schad, Thomas
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2017; Springer Nature B.V
• Subjects: Astrophysics and Astroparticles; Atmospheric Sciences; Automation; Corona; Datasets; Error analysis; Hough transformation; Integral transforms; Physics; Physics and Astronomy; Pixels; Rain; Solar corona; Solar physics; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics; Time series; Methods: pattern recognition; Active regions: structure; Chromosphere: active; Corona: structures
• ISSN: 0038-0938; 1573-093X
• DOI: 10.1007/s11207-017-1153-9

A technique is presented that automates the direction characterization of curvilinear features in multidimensional solar imaging datasets. It is an extension of the Rolling Hough Transform (RHT) technique presented by Clark, Peek, and Putman ( Astrophys. J. 789 , 82, 2014 ), and it excels at rapid quantification of spatial and spatiotemporal feature orientation even for applications with a low signal-to-noise ratio. It operates on a pixel-by-pixel basis within a dataset and reliably quantifies orientation even for locations not centered on a feature ridge, which is used here to derive a quasi-continuous map of the chromospheric fine-structure projection angle. For time-series analysis, a procedure is developed that uses a hierarchical application of the RHT to automatically derive the apparent motion of coronal rain observed off-limb. Essential to the success of this technique is the formulation presented in this article for the RHT error analysis as it provides a means to properly filter results.