SJET: An Interactive Solar Jet Extraction Tool
Song Tan, Alexander Warmuth, Fr\'ed\'eric Schuller, Yuandeng Shen, Yue Fang, Jake A. J. Mitchell, Zedong Liu

TL;DR
SJET is an interactive Python tool that automates solar jet feature extraction, improving consistency and enabling large-scale statistical analysis of solar jets from high-resolution solar observations.
Contribution
Introduces SJET, a novel interactive tool combining multiple algorithms for accurate, standardized solar jet feature extraction from diverse observational data.
Findings
Effective across different observational conditions.
Good agreement with traditional analysis methods.
Dependent on user-defined parameters.
Abstract
Solar jets are dynamic collimated plasma flows in the solar atmosphere that play crucial roles in coronal heating and solar wind acceleration. Their complex and diverse morphologies pose significant challenges for developing universal algorithms for automatic identification and extraction, particularly for on-disk jets affected by projection effects and background contamination. We present SJET, an interactive tool for solar jet feature extraction using multiple algorithms developed in Python that integrates five thresholding algorithms with morphological operations. SJET implements a novel method for identifying start and end points based on circular regions that objectively determines jet propagation direction by exploiting morphological asymmetry, combined with modeling the axis using quadratic B\'ezier curves for accurate extraction of geometric parameters including length, width,…
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