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Linear spectral filtering for feature enhancement in AVIRIS data from the forest ecosystem dynamics flightline in northern Maine

机译:北方森林生态系统动态飞行绳的Aviris数据中特征增强的线性谱滤波

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In this paper, we investigate the use of linear filtering techniques in the exploitation of hyperspectral imagery. In particular, we focus on applications of the simultaneous diagonalization (SD) filter to hyperspectral image analysis. The SD filter can be designed to enhance a particular feature with a known spectral response pattern and suppress undesired features. The filter is used to enhance surface features in two AVIRIS scenes acquired from the Forest Ecosystem Dynamics (FED) flightline on September 8, 1990. A spectral distance algorithm is also applied to this hyperspectral data to enhance surface targets with similar spectral response patterns. Although no detailed ground information was utilized, targets were selected by image interpretation methods and included an urban/disturbed site, and a wetland bog area, and a northern vegetation type (mixed hardwood). Both the SD filter and the spectral distance algorithm are able to effectively separate these classes of ground features from others.
机译:在本文中,我们调查了线性滤波技术在高光谱图像开发中的使用。特别是,我们专注于同时对角线化(SD)滤波器到高光谱图像分析的应用。 SD滤波器可以设计成增强具有已知光谱响应图案的特定特征,并抑制不需要的特征。该过滤器用于增强1990年9月8日从森林生态系统动态(Fed)FlightLine获取的两个Aviris场景中的表面特征。光谱距离算法也应用于该高光谱数据,以增强具有相似频谱响应模式的表面目标。虽然没有使用详细的地面信息,但是通过图像解释方法选择目标,并包括城市/受扰动的地点,以及湿地沼泽区域,以及北部植被类型(混合硬木)。 SD滤波器和频谱距离算法都能够有效地将这些类与其他特征分开。

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