Mitigation of variable illumination effects in hyperspectral imagery

减轻高光谱图像中的可变照明效应

• 批准号: 104941
• 金额: $ 2.64万
• 依托单位: 2 EXCEL GEO LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=104941
• 关键词: Mitigation; variable; illumination; effects; hyperspectral

"This project will conduct a feasibility study aimed at improving the operational effectiveness (i.e. reduce costs, increase envelope, improve exploitation) of airborne hyperspectral remote sensing. The key objective will be to develop and evaluate techniques to mitigate the effects of variable illumination, in particular cloud shadow, on the recovery of surface reflectance. The techniques will be developed and tested on a significant volume of empirical and modelled data. The main areas of focus are;* To determine if the at-sensor radiance spectra reveal information regarding the local illumination conditions via radiative modelling and empirical data collection. This seeks to identify traits embedded in the at-sensor radiance that may provide information regarding the local illumination conditions. Existing techniques include empirically derived 'shadow indices' that use a few selected bands; the innovation is to examine the entire spectrum to seek an improved technique.* To exploit the statistics of the illumination field (determined above), including in shadow, to devise a mitigation approach. This approach is an extension of previously published 'invariance' techniques designed to be robust to varying atmospheric and environmental factors. These determine the subspace which contains the majority of variance caused by these factors. These unwanted dimensions are then 'projected out' of the at-sensor signature. These techniques have been limited to clear sky conditions by 'off-the-shelf' radiative transfer models. The innovation is to include the attenuating effects of cloud in the determination of an invariant subspace thus enabling robust exploitation over a wider range of environmental conditions.* To develop a empirical correction technique exploiting time series, cloud-free airborne and satellite imagery. This approach is motivated by the increasing regularity and availability of satellite imagery. Published techniques crudely replace shadowed pixels with the corresponding cloud-free pixel from an image acquired at around the same time. This approach is not suitable to be applied to sources with differing spectral and spatial response (i.e. satellite and airborne). The innovation is to develop a technique in which a correction for cloud shadow in the hyperspectral image is derived from that of a satellite (e.g. Sentinel-2) multi-spectral image."

“该项目将进行一项可行性研究，旨在提高航空高光谱遥感的业务有效性(即降低成本、增加包络、改进开发)。关键目标将是开发和评价各种技术，以减轻可变光照，特别是云层阴影对恢复表面反射率的影响。这些技术将在大量的经验数据和模型数据上进行开发和测试。主要的重点领域是；*通过辐射建模和经验数据收集，确定AT传感器的辐射光谱是否揭示了关于当地照明条件的信息。这试图识别嵌入在AT传感器辐射中的特征，这些特征可以提供关于局部照明条件的信息。现有的技术包括使用几个选定波段的经验式得出的“阴影指数”；创新之处在于检查整个光谱以寻求改进的技术。*利用包括阴影在内的照明场的统计数据来设计一种缓解方法。这种方法是先前发表的“不变性”技术的扩展，其设计目的是对不同的大气和环境因素保持稳健。这些因素决定了包含由这些因素引起的大部分方差的子空间。然后，这些不需要的维度就会从at-ensors签名中‘投影出来’。这些技术被现有的辐射传输模型限制在晴朗的天空条件下。创新之处在于将云的衰减效应包括在一个不变子空间的确定中，从而能够在更广泛的环境条件下进行强有力的开发。*开发一种利用时间序列、无云的航空和卫星图像的经验校正技术。这种做法的动机是卫星图像的日益规律性和可获得性。已发表的技术粗暴地将阴影像素替换为几乎同时获取的图像中相应的无云像素。这种方法不适合应用于光谱和空间响应不同的源(即卫星和机载)。创新是开发一种技术，其中对高光谱图像中的云阴影的校正是从卫星(例如哨兵2号)多光谱图像的校正得出的。