An Endmember Extraction Method Based on Artificial Bee Colony Algorithms for Hyperspectral Remote Sensing Images
文献类型：期刊论文
| 作者 | Sun, Xu1; Yang, Lina1; Zhang, Bing1; Gao, Lianru1; Gao, Jianwei1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 7期号:12页码:1695-1713 |
| 关键词 | hyperspectral remote sensing artificial bee colony algorithm endmember extraction spectral unmixing |
| 通讯作者 | Zhang, B (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China. |
| 英文摘要 | Mixed pixels are common in hyperspectral remote sensing images. Endmember extraction is a key step in spectral unmixing. The linear spectral mixture model (LSMM) constitutes a geometric approach that is commonly used for this purpose. This paper introduces the use of artificial bee colony (ABC) algorithms for spectral unmixing. First, the objective function of the external minimum volume model is improved to enhance the robustness of the results, and then, the ABC-based endmember extraction process is presented. Depending on the characteristics of the objective function, two algorithms, Artificial Bee Colony Endmember Extraction-RMSE (ABCEE-R) and ABCEE-Volume (ABCEE-V) are proposed. Finally, two sets of experiment using synthetic data and one set of experiments using a real hyperspectral image are reported. Comparative experiments reveal that ABCEE-R and ABCEE-V can achieve better endmember extraction results than other algorithms when processing data with a low signal-to-noise ratio (SNR). ABCEE-R does not require high accuracy in the number of endmembers, and it can always obtain the result with the best root mean square error (RMSE); when the number of endmembers extracted and the true number of endmembers does not match, the RMSE of the ABCEE-V results is usually not as good as that of ABCEE-R, but the endmembers extracted using the former algorithm are closer to the true endmembers. |
| 研究领域[WOS] | Remote Sensing |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000367534000029 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38049]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Sun, Xu 2.Yang, Lina 3.Zhang, Bing 4.Gao, Lianru 5.Gao, Jianwei] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sun, Xu,Yang, Lina,Zhang, Bing,et al. An Endmember Extraction Method Based on Artificial Bee Colony Algorithms for Hyperspectral Remote Sensing Images[J]. REMOTE SENSING,2015,7(12):1695-1713. |
| APA | Sun, Xu,Yang, Lina,Zhang, Bing,Gao, Lianru,&Gao, Jianwei.(2015).An Endmember Extraction Method Based on Artificial Bee Colony Algorithms for Hyperspectral Remote Sensing Images.REMOTE SENSING,7(12),1695-1713. |
| MLA | Sun, Xu,et al."An Endmember Extraction Method Based on Artificial Bee Colony Algorithms for Hyperspectral Remote Sensing Images".REMOTE SENSING 7.12(2015):1695-1713. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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