Feature-Area Optimization: A Novel SAR Image Registration Method
This is an incremental improvement for multi-temporal SAR image registration in remote sensing applications.
The paper tackles SAR image registration by proposing Feature-Area Optimization (FAO), which reconstructs an area-based model into three uncertain factors determined via a novel SIFT-DRS feature extraction method, achieving accurate and efficient registration in experiments.
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.