基于端元的场景大气检索(EMISAR)

E. M. Winter
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引用次数: 2

摘要

航空航天公司的现场大气补偿(ISAC)算法提供了仅使用图像数据本身就可以消除大气对长波红外(LWIR)高光谱数据的影响的能力。ISAC算法试图在数据中找到黑体像素,然后使用已知的黑体光谱特征对数据进行校正。LWIR数据中最常见的黑体例子是植被和水。虽然ISAC算法已经成功地应用于各种各样的数据,但当场景中很少或没有植被或水时,ISAC算法可能会失败。在这种情况下,算法会找到一些其他的材料作为黑体,这可能导致在校正过程中出现错误。EMISAR算法基于ISAC方法,但提供了一种允许使用其他已知材料的替代方法。首先将数据转换为视发射率,然后在场景中找到光谱端元。这种方法的优点是可以在场景中找到真正的黑体(具有高分数丰度的植被和水像素),并且可以自主地完成。如果已知某些场景材料的光谱,它也可以用于没有植被的场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Endmember-based in-scene atmospheric retrieval (EMISAR)
The Aerospace Corp. in-scene atmospheric compensation (ISAC) algorithm offers the ability to remove the effects of the atmosphere on long wave infrared (LWIR) hyperspectral data using only the image data itself. The ISAC algorithm attempts to find blackbody pixels in the data and then uses the known spectral signature of a blackbody to correct the data. The most common examples of blackbodies in LWIR data are vegetation and water. While it has been applied successfully to a wide variety of data, the ISAC algorithm can fail when there is little or no vegetation or water in the scene. In this case, the algorithm will find some other material as a blackbody and this can result in an error in the correction process. The EMISAR algorithm is based on the ISAC method but offers an alternative approach that allows the use of other known materials. The data is first transformed to apparent emissivity, and then the spectral endmembers are found in the scene. This approach has the advantage of finding the true blackbodies in the scene (vegetation and water pixels with high fractional abundances), and can do it autonomously. It also can be used with scenes without vegetation, if the spectrum of some scene material is known.
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