文章基本信息

标题：ABOUT THE APPLICATIONS OF UNMIXING-BASED DENOISING FOR HYPERSPECTRAL DATA
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作者：D. Cerra ; R. Müller ; P. Reinartz 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2013
卷号：XL-1/W3
页码：103-106
DOI：10.5194/isprsarchives-XL-1-W3-103-2013
出版社：Copernicus Publications
摘要：Unmixing-based Denoising is a recently defined method which exploits spectral unmixing to recover bands characterized by a low Signal-to-Noise Ratio in a hyperspectral scene. The output of the unmixing process, which aims at decomposing each image element in signals typically related to pure materials, is inferred into the pixelwise reconstruction of a given band, ignoring the residual vector which is mainly characterized by undesired atmospheric influences and sensor-induced noise. The reconstructed images exhibit both high visual quality and reduced spectral distortions. This paper analyses the main problems that must be taken into account when applying this technique to real data. Special attention is given to the reference spectra used in the linear mixing model, which should be selected in order to keep the informational content of a given band unaltered in the reconstruction step
关键词：Hyperspectral remote sensing; denoising; spectral unmixing