Multi-Dimensional Fusion of Spectral and Polarimetric Images Followed by Pseudo-Color Algorithm Integration and Mapping in HSI Space | |
Guo, Fengqi1,2; Zhu, Jingping1; Huang, Liqing2; Li, Feng1; Zhang, Ning3; Deng, Jinxin1; Li, Haoxiang1; Zhang, Xiangzhe1; Zhao, Yuanchen1; Jiang, Huilin4; Hou, Xun1 | |
作者部门 | 光谱成像技术研究室 |
2024-04 | |
发表期刊 | REMOTE SENSING
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ISSN | 2072-4292 |
卷号 | 16期号:7 |
产权排序 | 3 |
摘要 | Spectral-polarization imaging technology plays a crucial role in remote sensing detection, enhancing target identification and tracking capabilities by capturing both spectral and polarization information reflected from object surfaces. However, the acquisition of multi-dimensional data often leads to extensive datasets that necessitate comprehensive analysis, thereby impeding the convenience and efficiency of remote sensing detection. To address this challenge, we propose a fusion algorithm based on spectral-polarization characteristics, incorporating principal component analysis (PCA) and energy weighting. This algorithm effectively consolidates multi-dimensional features within the scene into a single image, enhancing object details and enriching edge features. The robustness and universality of our proposed algorithm are demonstrated through experimentally obtained datasets and verified with publicly available datasets. Additionally, to meet the requirements of remote sensing tracking, we meticulously designed a pseudo-color mapping scheme consistent with human vision. This scheme maps polarization degree to color saturation, polarization angle to hue, and the fused image to intensity, resulting in a visual display aligned with human visual perception. We also discuss the application of this technique in processing data generated by the Channel-modulated static birefringent Fourier transform imaging spectropolarimeter (CSBFTIS). Experimental results demonstrate a significant enhancement in the information entropy and average gradient of the fused image compared to the optimal image before fusion, achieving maximum increases of 88% and 94%, respectively. This provides a solid foundation for target recognition and tracking in airborne remote sensing detection. |
关键词 | spectral images polarimetric images pseudo-color mapping remote sensing |
DOI | 10.3390/rs16071119 |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:001201154500001 |
出版者 | MDPI |
EI入藏号 | 20241615921118 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/97394 |
专题 | 光谱成像技术研究室 |
通讯作者 | Zhu, Jingping |
作者单位 | 1.Xi An Jiao Tong Univ, Minist Educ, Key Lab Phys Elect & Devices, Shaanxi Key Lab Informat Photon Tech, Xian 710049, Peoples R China 2.Xi An Jiao Tong Univ, Sch Phys, Minist Educ, Key Lab,Non Equilibrium Condensed Matter & Quantum, Xian 710049, Peoples R China 3.Xian Inst Opt & Precis Mech CAS, Key Lab Spectral Imaging Technol, Xian 710119, Peoples R China 4.Changchun Univ Sci & Technol, Natl & Local Joint Engn Res Ctr Space Optoelect Te, Changchun 130022, Peoples R China |
推荐引用方式 GB/T 7714 | Guo, Fengqi,Zhu, Jingping,Huang, Liqing,et al. Multi-Dimensional Fusion of Spectral and Polarimetric Images Followed by Pseudo-Color Algorithm Integration and Mapping in HSI Space[J]. REMOTE SENSING,2024,16(7). |
APA | Guo, Fengqi.,Zhu, Jingping.,Huang, Liqing.,Li, Feng.,Zhang, Ning.,...&Hou, Xun.(2024).Multi-Dimensional Fusion of Spectral and Polarimetric Images Followed by Pseudo-Color Algorithm Integration and Mapping in HSI Space.REMOTE SENSING,16(7). |
MLA | Guo, Fengqi,et al."Multi-Dimensional Fusion of Spectral and Polarimetric Images Followed by Pseudo-Color Algorithm Integration and Mapping in HSI Space".REMOTE SENSING 16.7(2024). |
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Multi-Dimensional Fu(8479KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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