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Registration algorithm based on line-intersection-line for satellite remote sensing images of urban areas

  • Siying Liu
  • , Jie Jiang*
  • *Corresponding author for this work
  • Beihang University
  • Key Laboratory of Precision Opto-Mechatronics Technology (Ministry of Education)
  • BUAA-CCMU Advanced Innovation Center for Big Data-based Precision Medicine

Research output: Contribution to journalArticlepeer-review

Abstract

Image registration is an important step in remote sensing image processing, especially for images of urban areas,which are often used for urban planning, environmental assessment, and change detection. Urban areas have many artificial objects whose contours and edges provide abundant line features. However, the locations of line endpoints are greatly affected by large background variations. Considering that line intersections remain relatively stable and have high positioning accuracy even with large background variations, this paper proposes a high-accuracy remote sensing image registration algorithm that is based on the line-intersection-line (LIL) structure, with two line segments and their intersection. A double-rectangular local descriptor and a spatial relationship-based outlier removal strategy are designed on the basis of the LIL structure. First, the LILs are extracted based on multi-scale line segments. Second, LIL local descriptors are built with pixel gradients in the LIL neighborhood to realize initial matching. Third, the spatial relations between initial matches are described with the LIL structure and simple affine properties. Finally, the graph-based LIL outlier removal strategy is conducted and incorrect matches are eliminated step by step. The proposed algorithm is tested on simulated and real images and compared with state-of-the-art methods. The experiments prove that the proposed algorithm can achieve sub-pixel registration accuracy, high precision, and robust performance even with significant background variations.

Original languageEnglish
Article number1400
JournalRemote Sensing
Volume11
Issue number12
DOIs
StatePublished - 1 Jun 2019

Keywords

  • Background variations
  • Image registration
  • Line-intersection-line (LIL)
  • Remote sensing
  • Urban areas

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