A High‐Resolution Transmission Electron Microscopy Image Processing Workflow for Extracting Aromatic Lattice Fringes in High‐Rank Coal

Quantitative extraction of aromatic lattice fringes from high-resolution transmission electron microscopy (HRTEM) images is essential for the nanoscale characterization of high-rank coal. However, variations in image processing strategies may introduce structural biases into the extracted lattice fringe networks, while the effects of individual processing steps remain insufficiently evaluated. In this study, an image processing workflow was developed for lattice fringe extraction from high-resolution transmission electron microscopy images of high-rank coal. The workflow integrates frequency-domain enhancement, contrast optimization, threshold segmentation, skeletonization, and skeleton refinement. Comparative experiments were performed to evaluate the effects of enhancement strategies, segmentation methods, and skeleton cleaning procedures on the extracted lattice fringe networks. Three topological parameters, including endpoint density, junction density, and average branch length, were introduced to assess skeleton integrity, abnormal connections, and structural continuity. The results demonstrate that selective frequency-domain enhancement is critical for maintaining stable skeleton topology, whereas spatial-domain smoothing increases non-physical connections and fragmentation. Although global Otsu thresholding produces comparable geometric measurements, differences remain in topological characteristics, indicating that geometric parameters alone cannot fully describe lattice fringe networks. Length-based filtering effectively removes artifacts with limited influence on network connectivity, while junction removal disrupts the structural framework of the skeleton. The proposed workflow provides a robust approach for quantitative analysis of lattice fringe networks and offers a methodological basis for reliable microscopic characterization of carbon materials.