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 language | English |
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Article number | 7372384 |
Pages (from-to) | 242-246 |
Number of pages | 5 |
Journal | IEEE Geoscience and Remote Sensing Letters |
Volume | 13 |
Issue number | 2 |
DOIs | |
Publication status | Published - 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