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Fusion of airborne hyperspectral and multispectral images

机译:机载高光谱和多光谱图像的融合

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Abstract: The multi-sensor multi-resolution technique (MMT) was applied to fuse a multispectral image obtained by the multispectral scanner DAEDALUS-1268 with the resolution of 6 m and a hyperspectral image obtained by the imaging spectrometer DAIS-7915. The spatial resolution of the DAIS- 7915 image was additionally degraded to 24 m in order to simulate multi-sensor data fusion with a very different sensor resolution, as is typical for satellite sensors. Both sensors had been operated simultaneously on one aircraft. The MMT algorithm includes: (1) (unsupervised) classification of the multispectral image and mapping the classes with the high resolution of the multispectral scanner, (2) retrieval of the hyperspectral signatures of these classes from the hyperspectral image, and (3) generation of the merged image which combines the pixel size of the multispectral scanner and the spectral bands of the imaging spectrometer. Additional low-pass correction of the merged image allowed us to increase significantly its accuracy. The minimal pixel error of 6.9% was obtained when the classification was performed with 256 spectral classes. !21
机译:摘要:应用多传感器多分辨率技术(MMT)将多光谱扫描仪DAEDALUS-1268获得的多光谱图像(分辨率为6 m)与成像光谱仪DAIS-7915获得的高光谱图像融合。 DAIS- 7915图像的空间分辨率另外降低到24 m,以模拟具有非常不同的传感器分辨率的多传感器数据融合,这对于卫星传感器来说是典型的。两个传感器在一架飞机上同时运行。 MMT算法包括:(1)多光谱图像的(无监督)分类,并以多光谱扫描仪的高分辨率映射类别,(2)从高光谱图像中检索这些类别的高光谱特征,以及(3)生成合并后的图像的图像,它结合了多光谱扫描仪的像素大小和成像光谱仪的光谱带。合并图像的其他低通校正使我们可以显着提高其准确性。使用256个光谱类别进行分类时,获得了6.9%的最小像素误差。 !21

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