Acta Optica Sinica, Volume. 36, Issue 1, 130003(2016)
Independent Component Feature Extraction Method for Hyperspectral Image Based on Negentropy Statistics in Moving Windows
An independent component feature extraction method based on negentropy statistics in moving windows is presented for the ordering of the independent components, and applied in target detection. A small window is moved in the two dimensional space of the independent component image. Data from each window is evaluated by negentropy approximation statistics using nonpolynomial function. The largest one of all of the evaluations is considered as the result evaluation, and the component images are ordered by the result evaluation. The two- value figure from the chosen component is made by histogram zero value split method, realizing target detection from the feature extracted independent components. The experiment results show that the independent component feature extraction method based on negentropy statistics in moving windows can avoid the influence of wild values, also select the valid components with small target, and benefit rapid detection of interested target.
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Zhu Yuanyuan, Gao Jiaobo, Gao Zedong. Independent Component Feature Extraction Method for Hyperspectral Image Based on Negentropy Statistics in Moving Windows[J]. Acta Optica Sinica, 2016, 36(1): 130003
Category: Spectroscopy
Received: Jun. 25, 2015
Accepted: --
Published Online: Dec. 31, 2015
The Author Email: Yuanyuan Zhu (zhuyuanme@126.com)