Saliency based visualization of hyper-spectral images

Haris Ahmad Khan, M. Khan, K. Khurshid, J. Chanussot
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引用次数: 15

Abstract

The problem with visualization of hyper-spectral images on tri-stimulus displays arises from the fact that they contain hundreds of spectral bands while generally used display devices support only three bands/channels namely blue, green and red. Therefore, for visualization a hyper-spectral (HS) image has to be reduced to three bands. The main challenge while performing this band reduction is to retain and display the maximum information available in a hyper-spectral image. Human visual system focuses attention on certain regions in images called “salient regions”. Therefore to provide a comprehensive representation of hyper-spectral data on tri-stimulus displays we propose to use a weighted fusion method of saliency maps and hyper-spectral bands. The efficacy of the proposed algorithm has been demonstrated by tests on both urban and countryside images of AVIRIS and ROSIS sensors.
基于显著性的高光谱图像可视化
在三刺激显示器上显示高光谱图像的问题在于它们包含数百个光谱波段,而通常使用的显示设备只支持三个波段/通道,即蓝、绿和红。因此,为了使高光谱(HS)图像可视化,必须将其压缩到三个波段。进行这种波段压缩的主要挑战是保留和显示高光谱图像中可用的最大信息。人类视觉系统将注意力集中在图像中的特定区域,称为“显著区域”。因此,为了提供三刺激显示器上的高光谱数据的综合表示,我们提出使用显著性图和高光谱带的加权融合方法。通过对AVIRIS和ROSIS传感器的城市和农村图像进行测试,证明了该算法的有效性。
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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