An Iterative Deep Homography Network Based on Correlation Content Calculation for High-Precision Image Registration of Fly-Capture Imaging System

This article presents a novel iterative deep homography network based on correlation content calculation (IDHN-CCC) for high-precision image registration of a fly-capture imaging system. The new high-precision fly-capture imaging (HFI) system is designed to obtain high-resolution images of radar microwave components (RMCs) and improve surface defect detection efficiency and autonomy while reducing hardware costs. The HFI consists of four subsystems: image acquisition mechanism, control system, image registration algorithm, and software system, which could achieve clear capture and precise imaging of RMC at high speed. The system adopts the IDHN-CCC algorithm to reduce the impact of motion errors on imaging stitching quality, which does not rely on precise camera motion positioning and coordinate transformation to achieve high-precision registration of multiple continuous shooting images. The experimental studies demonstrated the advantages of the IDHN-CCC-based HFI, which can achieve RMC images in low overlap rate fly-capture scenes with high registration accuracy.