Synchronic coronal hole mapping using multi-instrument EUV images: Data preparation and detection method

TL;DR

This paper presents an automated method for mapping coronal holes using synchronized multi-instrument EUV images, with advanced preprocessing and segmentation techniques, and provides data and tools for the solar physics community.

Contribution

It introduces a robust preprocessing pipeline and a simplified segmentation algorithm for consistent coronal hole detection across multiple EUV instruments.

Findings

Enhanced coronal hole detection accuracy due to improved preprocessing.

Availability of synchronized EUV and coronal hole maps at 6-hour cadence.

Open-source code and data products for community use.

Abstract

We describe a method for the automatic mapping of coronal holes (CH) using simultaneous multi-instrument EUV imaging data. Synchronized EUV images from STEREO/EUVI A&B 195A and SDO/AIA 193A are preprocessed, including PSF deconvolution and the application of data-derived intensity corrections that account for center-to-limb variations (limb brightening) and inter-instrument intensity normalization. We systematically derive a robust limb-brightening correction that takes advantage of unbiased long-term averages of data and respects the physical nature of the problem. The new preprocessing greatly assists in CH detection, allowing for the use of a simplified variable-connectivity two-threshold region growing image segmentation algorithm to obtain consistent detection results. We generate synchronic EUV and CH maps, and show a preliminary analysis of CH evolution. Several data and code products are made available to the community (www.predsci.com/chd): For the period of this study (06/10/2010 to 08/18/14) we provide synchronic EUV and coronal hole map data at 6-hour cadence, data-derived limb-brightening corrections for STEREO/EUVI A&B 195A and SDO/AIA 193A, and inter-instrument correction factors to equate their intensities. We also provide the coronal hole image segmentation code module (ezseg) implemented in both FORTRAN OpenMP and GPU-accelerated C-CUDA. A complete implementation of our coronal hole detection pipeline in the form of a ready-to-use MATLAB driver script euv2chm utilizing ezseg is also made available.