A Novel Region-Based Image Registration Method for Multisource Remote Sensing Images Via CNN

• Main Authors: Liang Zeng, Yanlei Du, Huiping Lin, Jing Wang, Junjun Yin, Jian Yang
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Subjects: Image registration; radar imaging
• Online Access: https://ieeexplore.ieee.org/document/9309405/

The comprehensive utilization of images from various satellite sensors can significantly increase the performance of remote sensing applications and has, therefore, attracted extensive research attention. One of the essential challenges that research encounters comes from multisource image registration. This article proposes a novel region-based image registration method for multisource images. The proposed method exploits the region features of input images, which provide more consistent and common information of the multisource data. The image region features are extracted based on image semantic segmentation using the deep convolutional neural network approach. The final registration result is a pixel-level output corresponding to the input images. The proposed registration scheme overcomes the limits of traditional feature extraction methods (e.g., point feature) adopted in previous registration schemes. Results indicate that the proposed method has good performance for the multisource remote sensing image registration and can serve as a building block for the fusion of multisource images.