New sparsity based pansharpening algorithms for hyperspectral images

C. Kwan, Bence Budavari, Minh Dao, Jin Zhou
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引用次数: 21

Abstract

In this paper, we present new sparsity based algorithms in generating a high resolution hyperspectral image by fusing a high resolution color image with a low resolution hyperspectral image. Mathematical formulation of the sparsity based approaches is presented. Comparison with other pansharpening algorithms using actual data has been carried out using two hyperspectral image data sets. Initial results are encouraging. Most importantly, the new sparsity formulation points to a new direction in generating high resolution hyperspectral images where the raw images may be noisy.
基于稀疏度的高光谱图像泛锐化新算法
在本文中,我们提出了一种新的基于稀疏度的算法,通过融合高分辨率彩色图像和低分辨率高光谱图像来生成高分辨率高光谱图像。给出了基于稀疏度方法的数学表达式。利用两组高光谱图像数据,与其他泛锐化算法进行了对比。初步结果令人鼓舞。最重要的是,新的稀疏性公式指出了生成高分辨率高光谱图像的新方向,其中原始图像可能有噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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