对比度(视觉)
遥感
光学
计算机科学
杂乱
光谱带
视野
近红外光谱
计算机视觉
空间频率
人工智能
物理
地质学
雷达
电信
作者
Patrick Leslie,Richard Cavanaugh,Shane Jordan,Lindsey Wiley,Eddie L. Jacobs,Ronald G. Driggers,Joseph Conroy
出处
期刊:Applied Optics
[The Optical Society]
日期:2024-02-08
卷期号:63 (7): 1839-1839
被引量:3
摘要
The spectral information contained in the reflective imaging bands can be exploited for specific tasks. Whether targeting or mapping, the visible (VIS), near-infrared (NIR), shortwave infrared (SWIR), extended shortwave infrared (eSWIR) bands perform very differently for every application. For any imaging project, high contrast is very important for good imagery. High contrast leads to more recognizable features within a scene and easier identifiable objects. For mapping, good background scene contrast gives prominent features more detail and their locations can be easily identified. For targeting, low background scene contrast reduces clutter, making it easier to detect objects of interest. The VIS, NIR, SWIR, and eSWIR bands are popular reflective bands to design daytime imaging systems for either task. Deciding on which band will have the best contrast for a specific task is one of the first things to study when designing an imaging system. By measuring urban and rural scenes in terms of equivalent reflectivity (ER), a direct comparison of these four bands can show the utility they provide. The systems used to measure scene contrast are designed to have the same spatial resolution and field of view (FOV). With these instantaneous FOV (IFOV) matched systems, the variance and 1D power spectral densities (PSDs) provide a quantitative comparison for the contrast among the four bands. The ER differences and resulting contrast measured among these four bands show that the eSWIR has the highest contrast in both urban and rural scenes.
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