Abstract
Exactly extracting the stable feature of high resolution SAR image as well as matching it are two critical steps for the Antomatic regiestation systems. It is suggested that the Scale Invariant Feature Transform (SIFT) algorithm can be applied in the optical image registration systems and four representative experiments were performed to test its validity. It is found that SIFT can accurately register the high resolution SAR images than the traditional Harris in applicability and precision.
Highlights
Image registration [1,2] is the process of aligned two or more images in space from different time, different perspectives and different sensors, and it is a key step of multi-source image fusion or change detection
Automatic registration of SAR image especially High-resolution SAR image has not been well solved for a long time, sub-pixel registration accuracy is often required to achieve in practical applications
This article discusses the application of Scale Invariant Feature Transform (SIFT) feature extraction algorithm in high resolution SAR image registration
Summary
Image registration [1,2] is the process of aligned two or more images in space from different time, different perspectives and different sensors, and it is a key step of multi-source image fusion or change detection. It is difficult to apply in the high-resolution SAR images, because it is more sensitive to image gray, rotation and objectives’ increase or decrease, and its high complexity computation of using all points of regional information The key of another registration method based feature is to establish the key points, lines or other geometric corresponding relationship. This article discusses the application of SIFT feature extraction algorithm in high resolution SAR image registration. According to qualitative and quantitative analysis, SIFT can accurately register the high resolution SAR images were acquired in the same ascending orbit, and it is better than Harris in applicability and precision, and analysis limitations of the two algorithms
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