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

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.