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首页> 外文会议>Conference on Image Processing: Algorithms and Systems III; 20040119-20040121; San Jose,CA; US >Physically Motivated Correlation Formalism in Hyperspectral Imaging
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Physically Motivated Correlation Formalism in Hyperspectral Imaging

机译：高光谱成像中的物理动机相关形式主义

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摘要

Most remote sensing data-sets contain a limiting number of independent spatial and spectral measurements, beyond which no effective increase in information is achieved. This paper presents a Physically Motivated Correlation Formalism (PMCF) ,which places both Spatial and Spectral data on an equivalent mathematical footing in the context of a specific Kernel, such that, optimal combinations of independent data can be selected from the entire Hypercube via the method of 'Correlation Moments'. We present an experimental and computational analysis of Hyperspectral data sets using the Michigan Tech VFTHSI [Visible Fourier Transform Hyperspectral Imager] based on a Sagnac Interferometer, adjusted to obtain high SNR levels. The captured Signal Interferograms of different targets - aerial snaps of Houghton and lab-based data (white light, He-Ne laser , discharge tube sources) with the provision of customized scan of targets with the same exposures are processed using inverse imaging transformations and filtering techniques to obtain the Spectral profiles and generate Hypercubes to compute Spectral/Spatial/Cross Moments. PMCF answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required for a particular target recognition.
机译：大多数遥感数据集包含有限数量的独立空间和光谱测量值，超过这些值则无法有效地增加信息。本文提出了一种物理动机相关形式主义（PMCF），该方法将空间和频谱数据都放置在特定内核上下文中的等效数学基础上，从而可以通过该方法从整个Hypercube中选择独立数据的最佳组合。 “相关时刻”。我们使用基于Sagnac干涉仪的密歇根州技术VFTHSI [可见傅里叶变换高光谱成像仪]，对高光谱数据集进行实验和计算分析，并对其进行调整以获得高SNR级别。使用逆成像变换和滤波处理捕获的不同目标的信号干涉图-霍顿的空中快照和基于实验室的数据（白光，氦氖激光器，放电管源），并提供定制的具有相同曝光的目标扫描，技术来获取光谱轮廓并生成超立方体来计算光谱/空间/交叉矩。 PMCF回答了应如何最佳采样整个超立方体的问题，并找到了特定目标识别所需的空间光谱像素数。

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