Magnetic Field-Constrained Ensemble Image Segmentation of Coronal Holes in Chromospheric Observations

Abstract

Coronal Holes (CHs) are large-scale, low-density regions in the solar atmosphere which may expel high-speed solar wind streams that incite hazardous, geomagnetic storms. Coronal and solar wind models can predict these high-speed streams and the performance of the coronal model can be validated against segmented CH boundaries. We present a novel method named Sub-Transition Region Identification of Ensemble Coronal Holes (STRIDE-CH) to address prominent challenges in segmenting CHs with Extreme Ultraviolet (EUV) imagery. Ground-based, chromospheric He I 10830 Å line imagery and underlying Fe I photospheric magnetograms are revisited to disambiguate CHs from filaments and quiet Sun, overcome obscuration by coronal loops, and complement established methods in the community which use space-borne, coronal EUV observations. Classical computer vision techniques are applied to constrain the radiative and magnetic properties of detected CHs, produce an ensemble of boundaries, and compile these boundaries in a confidence map that quantifies the likelihood of CH presence throughout the solar disk. This method is science-enabling towards future studies of CH formation and variability from a mid-atmospheric perspective.

23 pages, 7 figures

References in corpus (26)

• Array Programming with NumPy
• scikit-image: Image processing in Python
• The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package
• Coronal Holes
• The Sun's Global Photospheric and Coronal Magnetic Fields: Observations and Models
• The Open Flux Problem
• Automated Coronal Hole Detection using Local Intensity Thresholding Techniques
• Coronal Holes and Open Magnetic Flux over Cycles 23 and 24
• Automated Detection of EUV Polar Coronal Holes During Solar Cycle 23
• Statistical Analysis and Catalog of Non-polar Coronal Holes Covering the SDO-era using CATCH
• Synchronic coronal hole mapping using multi-instrument EUV images: Data preparation and detection method
• Automated Coronal Hole Identification via Multi-Thermal Intensity Segmentation
• Estimating Total Open Heliospheric Magnetic Flux
• Characteristics of Low-Latitude Coronal Holes near the Maximum of Solar cycle 24
• Segmentation of coronal holes in solar disk images with a convolutional neural network
• Measurements of EUV Coronal Holes and Open Magnetic Flux
• Photospheric magnetic structure of coronal holes
• Multi-channel coronal hole detection with convolutional neural networks
• Automated identification of coronal holes from synoptic EUV maps
• The Observational Uncertainty of Coronal Hole Boundaries in Automated Detection Schemes
• Segmentation of Coronal Holes Using Active Contours Without Edges
• Forecasting the Ambient Solar Wind with Numerical Models. II. An Adaptive Prediction System for Specifying Solar Wind Speed Near the Sun
• Statistical Evidence for Small-Scale Interchange Reconnection at a Coronal Hole Boundary
• Quantifying the Consistency and Characterizing the Confidence of Coronal Holes Detected by Active Contours without Edges (ACWE)
• Image-Optimized Coronal Magnetic Field Models
• Magnetic Field-Constrained Ensemble Image Segmentation of Coronal Holes in Chromospheric Observations

Cited by in corpus (1)

• Magnetic Field-Constrained Ensemble Image Segmentation of Coronal Holes in Chromospheric Observations