Feature-based groupwise registration of historical aerial images to present-day ortho-photo maps
作者：
Highlights：
• Groupwise image registration by sequentially registering pairs of images is error-prone in case of highly unreliable pairwise registrations.
• Hough voting spaces enable probabilistic pairwise registration estimations in order to identify the joint max-likelihood registration of all images.
• Framework for probabilistic groupwise registration process based on feature correspondences.
• Unlike previous groupwise registration work, the proposed method is able to jointly register images with arbitrary translational and rotational differences.
• Outperforms state-of-the-art for highly challenging registration of aerial WW2 images to present-day ortho-photo maps.
摘要
•Groupwise image registration by sequentially registering pairs of images is error-prone in case of highly unreliable pairwise registrations.•Hough voting spaces enable probabilistic pairwise registration estimations in order to identify the joint max-likelihood registration of all images.•Framework for probabilistic groupwise registration process based on feature correspondences.•Unlike previous groupwise registration work, the proposed method is able to jointly register images with arbitrary translational and rotational differences.•Outperforms state-of-the-art for highly challenging registration of aerial WW2 images to present-day ortho-photo maps.
论文关键词：Image registration,Geolocalization,Remote sensing,Optimization,Hough voting
论文评审过程：Received 31 July 2018, Revised 19 November 2018, Accepted 13 January 2019, Available online 17 January 2019, Version of Record 22 January 2019.
论文官网地址：https://doi.org/10.1016/j.patcog.2019.01.024
