Abstract
In order to detect targets from the hyper-spectral images captured by unmanned aerial vehicles, the images are moved into a new characteristic space with greater divisibility by making use of the manifold learning theory. On this basis, a furation impulse response (FIR) filter is developed. The output energy can be minimized after images passing through a FIR filter. The target pixel and the background pixel are distinguished according to the restrained conditions. This method can effectively suppress noises and detect sub-pixel targets in the hyper-spectral remote sensing image of unknown background spectrum.
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Foundation item: Supported by the National Basic Research Program of China (973 Program) (2006CB303000)
Biography: SHEN Yingchun, male, Ph.D. candidate, research direction: wireless sensor networks.
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Shen, Y., Jin, H. & Du, B. An improved method to detect remote sensing image targets captured by sensor network. Wuhan Univ. J. Nat. Sci. 16, 301–307 (2011). https://doi.org/10.1007/s11859-011-0754-7
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DOI: https://doi.org/10.1007/s11859-011-0754-7