کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
849940 | 909275 | 2013 | 4 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Algorithms of target detection on hyperspectral imagery Algorithms of target detection on hyperspectral imagery](/preview/png/849940.png)
With the development of airborne and spaceborne remote sensing from the 1980s, as a new and growing technology, hyperspectral imaging is widely used in different fields, such as military investigation, battlefield information acquisition, environmental monitoring, mineral exploration and public security. Because of the unique characteristic of acquiring spectral and spatial information simultaneously, it brings the hyperspectral detection advantages when dealing with target detection problem under complex conditions. Target detecting models of hyperspectral image are established, including the target subspace model and the probability statistical model. And several algorithms are introduced, which are based on original spectral features, sub-space projection and probability statistical model separately. Comparison shows that if the background includes fault objectives, GLRT is the best algorithm, and its SINR is the largest; on condition of anomaly target detection, LPTD is the best, and have a quite high SINR.
Journal: Optik - International Journal for Light and Electron Optics - Volume 124, Issue 23, December 2013, Pages 6341–6344