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A novel descriptor optimization method for multispectral images

机译:一种新的多光谱图像描述符优化方法

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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.
机译:本文提出了一种优化的多光谱图像描述符方法。所提出的方法基于LGHD(Log-Gabor直方图描述符)[1]。最初,从长波红外和可见光谱图像中检测所有特征点,并由LGHD进行描述,然后使用PCA(主成分分析)来缩小两个不同描述符的维数,最后使用优化的描述符来匹配这些点。实验结果表明,所提出的方法比LGHD具有更好的匹配性能。

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