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基于光谱导数检测高光谱图像中的物体
算法
2026/09/21
摘要：近年来，高光谱成像在场景中各种感兴趣物体的检测和映射方面已证明其重要性。已经开发出各种高光谱图像中 的物体检测方法，各有其优缺点。在本研究中，研究了一种包含光谱导数（一阶）和光谱信息散度的方法来检测高光谱 图像中的物体。在两个不同的 Hyperion 图像高光谱数据集上检验了检测方案的有效性。茶树 (Camellia sinensis) 和娑罗 树 (Shorea robusta)（纯像素）已被独立地检测为高光谱图像中的感兴趣物体，并且减少了假像素。所提出的方法将来可 能应用于混合像素的分类。
关键词：高光谱成像、光谱导数、光谱信息散度。
期刊：J Indian Soc Remote Sens
DOI：10.1007/s12524-016-0627-9
设备：GaiaField
Objects Detection in Hyperspectral Images Using Spectral Derivative
Abstract：In recent years hyperspectral imaging has proved its significance in the detection and mapping of various objects of interest in a scene. Various methods for object detection in hyperspectral images have been developed with their advantages and limitations. In the present study, a methodology comprising spectral derivative (first order) and spectral information divergence has been investigated for detection of objects in hyperspectral images. The efficacy of the detection scheme has been examined over two different hyperspectral data sets of Hyperion images. Tea plants (Camellia sinensis) and Sal trees (Shorea robusta) (pure pixels) have been detected as the objects of interest in the hyperspectral images independently with reduced false pixels. The proposed methodology may in future be applied for classification of mixed pixels.
Keywords：Hyperspectral imaging Spectral derivative Spectral information divergence.
