An automatic optical and SAR image registration method with iterative level set segmentation and SIFT

Although optical image registration methods have been successfully developed over the past decades, the registration of optical and synthetic aperture radar (SAR) images is still a challenging problem in remote sensing. Feature-based methods are considered to be more effective for multi-source image registration. However, almost all of these methods rely on the feature extraction algorithms. In this article, a simultaneous segmentation and feature-based registration method based on an iterative level set and scale-invariant feature transform (ILS-SIFT) is proposed. The core idea consists of three aspects: (1) an iterative procedure that combines image segmentation and matching is proposed to avoid registration failure caused by poor feature extraction; (2) a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features; and (3) an improved SIFT algorithm is employed to determine whether the registration was successful. Experimental results have shown the effectiveness and universality of the proposed method.

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