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 multi-temporal SAR images accurately and efficiently.
@article{arxiv.1602.05660,
title = {Feature-Area Optimization: A Novel SAR Image Registration Method},
author = {Fuqiang Liu and Fukun Bi and Liang Chen and Hao Shi and Wei Liu},
journal= {arXiv preprint arXiv:1602.05660},
year = {2016}
}