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A Modified Local Binary Pattern Descriptor for SAR Image Matching

机译:SAR图像匹配的改进局部二值模式描述符

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摘要

Image matching is an important step which is taken in most applications of synthetic aperture radar (SAR) images. In this letter, a method is proposed for SAR image matching which introduces a modified local binary pattern (LBP) as a descriptor. Multitextural feature LBP (MTF-LBP) uses the gray-level cooccurrence matrix to increase image texture information. MTF-LBP creates bit plane for each point candidate for matching. Then, using hamming distance, true matches are determined. Experiments are conducted on four spaceborne SAR image pairs including Radarsat-2, TerraSAR-X, ALOS-PALSAR, and Sentinel-1. The proposed method is compared with five common LBP approaches. The results indicate that the proposed method has a better performance in terms of the number of true matches.
机译:图像匹配是合成孔径雷达(SAR)图像大多数应用中迈出的重要一步。在这封信中,提出了一种用于SAR图像匹配的方法,该方法引入了改进的局部二进制模式(LBP)作为描述符。多纹理特征LBP(MTF-LBP)使用灰度共生矩阵来增加图像纹理信息。 MTF-LBP为每个要匹配的点创建位平面。然后,使用汉明距离确定真正的匹配。在包括Radarsat-2,TerraSAR-X,ALOS-PALSAR和Sentinel-1在内的四个星载SAR图像对上进行了实验。将该方法与五种常见的LBP方法进行了比较。结果表明,该方法在真实匹配数方面具有更好的性能。

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