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An automatic optical and SAR image registration method with iterative level set segmentation and SIFT
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DOI：10.1080/01431161.2015.1070321.png)
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Abstract
En 中文
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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