Feature-Area Optimization: A Novel SAR Image Registration Method

Fuqiang Liu, Fukun Bi, Liang Chen, Hao Shi, Wei Liu

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

This letter proposes a synthetic aperture radar (SAR) image registration method named feature-area optimization (FAO). First, the traditional area-based optimization model is reconstructed and decomposed into three key but uncertain factors: initialization, slice set, and regularization. Next, structural features are extracted by scale-invariant feature transform (SIFT) in dual-resolution space (SIFT-DRS), a novel SIFT-like method dedicated to FAO. Then, the three key factors are determined based on these features. Finally, solving the factor-determined optimization model can get the registration result. A series of experiments demonstrate that the proposed method can register multitemporal SAR images accurately and efficiently.

Original languageEnglish
Article number7372384
Pages (from-to)242-246
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume13
Issue number2
DOIs
Publication statusPublished - 1 Feb 2016

Keywords

  • Area-based optimization model
  • dual-resolution space
  • initialization and regularization
  • scale-invariant feature transform (SIFT)
  • synthetic aperture radar (SAR) image registration

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