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Hyperspectral imagery superresolution

机译:高光谱图像超分辨率

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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:尽管高光谱图像具有高光谱分辨率,但其空间分辨率却很低,这会对使用高光谱图像的应用产生不利影响。在这项研究中,代替了使用光谱图像的传统方法,而是使用了端成员的丰度来提高分辨率。在提出的方法中,首先,使用SISAL算法提取端成员。然后,使用FCLS估算丰度图。从低分辨率丰度图获得高分辨率丰度图,并基于总变化量最小化。最后,从高分辨率丰度图构建高分辨率高光谱图像。在真实的高光谱图像上测试了该方法。实验结果和比较分析表明了该方法的有效性。

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