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Hyperspectral imagery superresolution

机译:高光谱图像超级化

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摘要

Despite their high spectral resolution, hyperspectral images have low spatial resolution which adversely affects the applications that use hyperspectral images. In this study, instead of the traditional way of using spectral images, abundances of the endmembers are used in resolution enhancement. In the proposed method, first, endmembers are extracted with the SISAL algorithm. Then, the abundance maps are estimated using FCLS. From the low resolution abundance maps, high resolution abundance maps are obtained with a total variation based minimization. Finally, high resolution hyperspectral images are constructed from high resolution abundance maps. The proposed method is tested on real hyperspectral images. The experimental results and comparative analysis show the effectiveness of the proposed method.
机译:尽管它们的高光谱分辨率,但高光谱图像具有低空间分辨率,这对使用高光谱图像的应用产生不利影响。在本研究中,代替使用光谱图像的传统方式,终端用纤特的丰富用于分辨率增强。在所提出的方法中,首先,用SISAL算法提取终端。然后,使用FCLS估计丰度映射。从低分辨率丰度图,获得高分辨率丰度图,具有基于总变化的最小化。最后,高分辨率高光谱图像由高分辨率丰度图构成。所提出的方法在实际高光谱图像上进行测试。实验结果和比较分析表明了该方法的有效性。

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