Joint spatial constrained energy minimization for gas identification in hyperspectral imaging
文献类型：期刊论文
| 作者 | Ning, Zhiqiang1,2; Liu, Jiaxiang2 ; Xu, Haichun1,2; Miao, Junfang1,2; Wang, Canlong1,2; Pan, Ying2; Li, Zhengang2; Fang, Yonghua1,2
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| 刊名 | OPTICS COMMUNICATIONS
 |
| 出版日期 | 2025 |
| 卷号 | 574 |
| 关键词 | Gas identification Hyperspectral imaging Constrained energy minimization Long-wave infrared Pattern recognition |
| ISSN号 | 0030-4018 |
| DOI | 10.1016/j.optcom.2024.131057 |
| 通讯作者 | Li, Zhengang(lzgyx@mail.ustc.edu.cn) |
| 英文摘要 | Hyperspectral gas identification plays a crucial role in a variety of applications ranging from environmental monitoring to national security. Constrained Energy Minimization (CEM) constitutes a pivotal approach in hyperspectral gas target identification, emphasizing the enhancement of target signal output energy and the suppression of background signal output energy through the design of specialized filters. However, conventional CEM algorithms present notable deficiencies, notably their failure to fully exploit spatial information in hyperspectral image target recognition and their ineffectiveness in detecting targets over extensive areas. To address these challenges, a hyperspectral gas identification method named Joint Spatial Constrained Energy Minimization (JSCEM) was introduced. This method incorporates adaptive weight constraints and employs "pseudo background spectrum" techniques, integrating spatial data to improve target discernment and refining the estimation accuracy of the background autocorrelation matrix. Experimental validations involving both simulated and manual data have shown that the JSCEM method offers marked improvements in the detection of large-area gas targets within hyperspectral image. Simulation data indicate that the detection performance of the JSCEM method is significantly enhanced compared to various existing CEM algorithms. Furthermore, measured data confirm that the JSCEM algorithm accurately identifies large gas targets in hyperspectral images, offering a precise approach to gas detection. This advancement is expected to be valuable in industries requiring accurate and efficient gas identification. |
| WOS关键词 | TARGET DETECTION |
| 资助项目 | National Natural Science Foundation of China[61875207] ; Anhui Key Research and Development Program[2023n06020057] |
| WOS研究方向 | Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:001313173000001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Anhui Key Research and Development Program |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/135266]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Li, Zhengang |
| 作者单位 | 1.Univ Sci & Technol China, Hefei 230026, Peoples R China 2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Key Lab Environm Opt & Technol, Hefei 230031, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ning, Zhiqiang,Liu, Jiaxiang,Xu, Haichun,et al. Joint spatial constrained energy minimization for gas identification in hyperspectral imaging[J]. OPTICS COMMUNICATIONS,2025,574. |
| APA | Ning, Zhiqiang.,Liu, Jiaxiang.,Xu, Haichun.,Miao, Junfang.,Wang, Canlong.,...&Fang, Yonghua.(2025).Joint spatial constrained energy minimization for gas identification in hyperspectral imaging.OPTICS COMMUNICATIONS,574. |
| MLA | Ning, Zhiqiang,et al."Joint spatial constrained energy minimization for gas identification in hyperspectral imaging".OPTICS COMMUNICATIONS 574(2025). |
入库方式： OAI收割
来源：合肥物质科学研究院
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