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Feature-Area Optimization: A Novel SAR Image Registration Method
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DOI：10.1109/LGRS.2015.2507982.png)
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摘要
En 中文
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.
Keyword:
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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16.4
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被引数:
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