Target detection for hyperspectral image based on multi-scale analysis

被引：2

作者：

Wang Y. ^{[1
]}

Huang S. ^{[2
]}

Liu Z. ^{[1
]}

Wang H. ^{[1
]}

Liu D. ^{[1
]}

机构：

[1] Xi’an Research Institute of Hi-Tech, Xi’an, 710025, Shanxi

[2] Xijing University, Xi’an

来源：

Journal of Optics (India) | 2017年 / 46卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Hyperspectral; Multi-scale analysis; Target detection; Tensor;

D O I：

10.1007/s12596-016-0334-5

中图分类号：

学科分类号：

摘要：

To further improve target detection performance of hyperspectral image, this paper presents a novel method named multi-scale analysis-based target detection (MATD). The proposed method first applies multi-scale wavelet analysis technology to extract multi-scale features of hyperspectral data. Then, these features are converted into a tensor form, and is processed and analyzed by using tensor analysis method. Through solving the tensor subspace, the reduced-dimension feature coefficients can be extracted. Finally, based on these feature coefficients, a better target detection result can be obtained by using the detection algorithm. Experimental results of real world hyperspectral data show that the proposed MATD method can effectively improve detection performance. © 2016, The Optical Society of India.

引用

页码：75 / 82

页数：7

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