A novel descriptor optimization method for multispectral images

Z. Fu, B. Luo, Chun Wu, Q. Qin
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引用次数: 1

Abstract

This paper presents an optimized descriptor method for multispectral images. The method proposed is based on LGHD (Log-Gabor Histogram Descriptor)[1]. Initially, all feature points are detected from Long wave Infrared and Visible spectrum images, and descripted by LGHD, then PCA (Principal Component Analysis) is used to reduce the dimension of the two different descriptors, finally the optimized descriptors are used to match the points. Experimental results show that proposed approach achieves a better matching performance than LGHD.
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一种新的多光谱图像描述子优化方法
提出了一种优化的多光谱图像描述符方法。提出的方法基于LGHD (Log-Gabor直方图描述符)[1]。首先从长波红外和可见光谱图像中检测到所有特征点,并对其进行LGHD描述,然后使用主成分分析(PCA)对两种不同描述符进行降维,最后使用优化后的描述符进行点匹配。实验结果表明,该方法比LGHD具有更好的匹配性能。
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