Multi-sensor optical remote sensing image registration based on Line-Point Invariant

Xianmin Wang, Qizhi Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Due to the different imaging modalities and acquisition time, keypoint-based registration methods often suffer from false matches of keypoints while utilizing to register the optical remote sensing images from multi-sensors. In this paper, we proposed a novel method based on Line-Point Invariant for the multi-sensor image registration. First, the line segments of the images are extracted, and then the salient line segments are detected depending upon the adaptive confidence. Subsequently, conjugate salient lines between the two images are identified as the registration primitives by the probability relaxation labelling approach. Second, we obtain the SIFT keypoints of the images and establish the matches of the keypoints based on the Line-Point Invariant via dual matching. Consequently, false keypoint matches are greatly reduced and the correct match rate is significantly enhanced. The experiments conducted on various multi-sensor images demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2364-2367
Number of pages4
ISBN (Electronic)9781509033324
DOIs
Publication statusPublished - 1 Nov 2016
Externally publishedYes
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • Line-Point Invariant
  • multi-sensor image registration
  • registration primitives

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