Fast and Robust Matching for Multimodal Remote Sensing Image Registration

• Published in: IEEE transactions on geoscience and remote sensing Vol. 57; no. 11; pp. 9059 - 9070
• Main Authors: Ye, Yuanxin, Bruzzone, Lorenzo, Shan, Jie, Bovolo, Francesca, Zhu, Qing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computational efficiency; Computer applications; Computing time; Fast Fourier transform (FFT); Fast Fourier transformations; Feature extraction; Fourier transforms; Frameworks; Frequency-domain analysis; Gradients; Histograms; Image detection; Image matching; Image registration; Lidar; multimodal remote sensing images; pixelwise feature representation; Remote sensing; Representations; Robustness; SAR (radar); Self-similarity; Shape; Synthetic aperture radar; Template matching

While image matching has been studied in remote sensing community for decades, matching multimodal data [e.g., optical, light detection and ranging (LiDAR), synthetic aperture radar (SAR), and map] remains a challenging problem because of significant nonlinear intensity differences between such data...