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Method for classifying a pixel of a hyperspectral image in a remote sensing application

机译:在遥感应用中对高光谱图像像素进行分类的方法

摘要

What is disclosed is a novel system and method for simultaneous spectral decomposition suitable for image object identification and categorization for scenes and objects under analysis. The present system captures different spectral planes simultaneously using a Fabry-Perot multi-filter grid each tuned to a specific wavelength. A method for classifying pixels in the captured image is provided. The present system and method finds its uses in a wide array of applications such as, for example, occupancy detection in a transportation management system and in medical imaging and diagnosis for healthcare management. The teachings hereof further find their uses in other applications where there is a need to capture a two dimensional view of a scene and decompose the scene into its spectral bands such that objects in the image can be appropriately identified.
机译:公开了一种用于同时频谱分解的新颖系统和方法,其适用于图像对象的识别以及对所分析的场景和对象的分类。本系统使用每个都调谐到特定波长的Fabry-Perot多滤光片栅格同时捕获不同的光谱平面。提供了一种用于对所捕获图像中的像素进行分类的方法。本系统和方法可在多种应用中找到其用途,例如,在运输管理系统中的占用检测以及在用于医疗保健管理的医学成像和诊​​断中。本文的教导在需要捕获场景的二维视图并将场景分解成其光谱带以使得可以适当地识别图像中的对象的其他应用中进一步找到它们的用途。

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