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摘要不同波段的极化合成孔径雷达(SAR)图像间的配准,是多波段极化SAR数据融合中的一个重要问题。该文从地物的极化散射机理出发,提出了一种适用于尺度不变特征变换(SIFT)配准算法的极化特征。该特征包含了地物目标主要散射成分的信息,并反映了其他弱散射成分的强度分布,可在不同波段极化SAR图像中保持稳定。实验结果表明: 与使用散射总功率(Span)实现多波段极化SAR图像配准的方法相比,该特征在不同波段下的差异较小; 使用SIFT算法配准后,该特征图像可得到更多的关键点和正确配准点,且配准点的分布较分散,从而有效地提高了多波段极化SAR图像的配准性能。
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| 关键词 ：合成孔径雷达,极化散射特征,尺度不变特征变换,图像配准 |
Abstract：The registration of multi-band polarimetric synthetic aperture radar (SAR) images is a key problem for image fusion. This paper presents a feature based on the polarimetric scattering mechanism for registration using the scale invariant feature transform (SIFT) algorithm. The feature represents information for the main scattering component and the influence of the other scattering components distribution and has good consistency for multi-band polarimetric SAR images. Tests demonstrate that the feature difference between multi-band polarimetric SAR images is less than the total scattered power (Span) difference. The SIFT algorithm is then used to get more key points, more correct registration points, and better spatial distribution of the correct registration points. The registration efficiency is remarkably increased by this feature.
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| Key words：synthetic aperture radar (SAR)polarimetric scattering featurescale invariant feature transform (SIFT)image registration |
| 收稿日期: 2013-05-31 出版日期: 2015-04-16 |
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| 基金资助:国家自然科学基金项目 (41171317) |
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