{"title":"基于陆基高光谱成像和典型伪装材料的半经验核驱动模型的光谱反射率拟合","authors":"Jiale Zhao","doi":"10.1051/jeos/2023045","DOIUrl":null,"url":null,"abstract":"Abstract: The reflectance of an object is a physical quantity that is related to a variety of factors such as wavelength, direction of light source, direction of detection, and weather conditions.If complete spectral information about the target is to be obtained, this can only be done by measuring the spectral reflectance in all angular directions. Obviously, this method of acquiring spectral data has the disadvantages of complex operation, low efficiency and poor timeliness in military applications. The Semi-Empirical kernel-driven model captures the main factors affecting the bidirectional reflective properties of an object and uses physically meaningful kernel parameters to characterise the reflective properties of an object. By measuring these kernel parameters and combining them with a small number of measurements, it is possible to extrapolate and fit the spectral reflectance of the target in all directions, improving the efficiency of information acquisition and processing. Semi-empirical kernel-driven models were initially used to study the composition and structure of vegetation and its spectral reflectance properties with some results. However, whether the Semi-empirical kernel-driven model can be effectively used to study the spectral reflectance properties of military materials has not been verified. This paper first introduces three commonly used semi-empirical kernel-driven models, namely RossThick-LiSparseR(RTLSR), RossThick-LiTransitN (RTLT) and RossThick-Roujean (RTR). Then, the spectral reflectance of four typical military materials was measured using an imaging spectrometer, and the fitting effects of different models were evaluated. Experiments show that the three semi-empirical kernel-driven models have good data fitting ability for different types of military materials.Overall, RTLSR model has the best data fitting ability and the best stability of inversion results.","PeriodicalId":674,"journal":{"name":"Journal of the European Optical Society-Rapid Publications","volume":"17 8","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spectral reflectance fitting based on land-based hyperspectral imaging and semi-empirical kernel-driven model for typical camouflage materials\",\"authors\":\"Jiale Zhao\",\"doi\":\"10.1051/jeos/2023045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract: The reflectance of an object is a physical quantity that is related to a variety of factors such as wavelength, direction of light source, direction of detection, and weather conditions.If complete spectral information about the target is to be obtained, this can only be done by measuring the spectral reflectance in all angular directions. Obviously, this method of acquiring spectral data has the disadvantages of complex operation, low efficiency and poor timeliness in military applications. The Semi-Empirical kernel-driven model captures the main factors affecting the bidirectional reflective properties of an object and uses physically meaningful kernel parameters to characterise the reflective properties of an object. By measuring these kernel parameters and combining them with a small number of measurements, it is possible to extrapolate and fit the spectral reflectance of the target in all directions, improving the efficiency of information acquisition and processing. Semi-empirical kernel-driven models were initially used to study the composition and structure of vegetation and its spectral reflectance properties with some results. However, whether the Semi-empirical kernel-driven model can be effectively used to study the spectral reflectance properties of military materials has not been verified. This paper first introduces three commonly used semi-empirical kernel-driven models, namely RossThick-LiSparseR(RTLSR), RossThick-LiTransitN (RTLT) and RossThick-Roujean (RTR). Then, the spectral reflectance of four typical military materials was measured using an imaging spectrometer, and the fitting effects of different models were evaluated. Experiments show that the three semi-empirical kernel-driven models have good data fitting ability for different types of military materials.Overall, RTLSR model has the best data fitting ability and the best stability of inversion results.\",\"PeriodicalId\":674,\"journal\":{\"name\":\"Journal of the European Optical Society-Rapid Publications\",\"volume\":\"17 8\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the European Optical Society-Rapid Publications\",\"FirstCategoryId\":\"4\",\"ListUrlMain\":\"https://doi.org/10.1051/jeos/2023045\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the European Optical Society-Rapid Publications","FirstCategoryId":"4","ListUrlMain":"https://doi.org/10.1051/jeos/2023045","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPTICS","Score":null,"Total":0}
Spectral reflectance fitting based on land-based hyperspectral imaging and semi-empirical kernel-driven model for typical camouflage materials
Abstract: The reflectance of an object is a physical quantity that is related to a variety of factors such as wavelength, direction of light source, direction of detection, and weather conditions.If complete spectral information about the target is to be obtained, this can only be done by measuring the spectral reflectance in all angular directions. Obviously, this method of acquiring spectral data has the disadvantages of complex operation, low efficiency and poor timeliness in military applications. The Semi-Empirical kernel-driven model captures the main factors affecting the bidirectional reflective properties of an object and uses physically meaningful kernel parameters to characterise the reflective properties of an object. By measuring these kernel parameters and combining them with a small number of measurements, it is possible to extrapolate and fit the spectral reflectance of the target in all directions, improving the efficiency of information acquisition and processing. Semi-empirical kernel-driven models were initially used to study the composition and structure of vegetation and its spectral reflectance properties with some results. However, whether the Semi-empirical kernel-driven model can be effectively used to study the spectral reflectance properties of military materials has not been verified. This paper first introduces three commonly used semi-empirical kernel-driven models, namely RossThick-LiSparseR(RTLSR), RossThick-LiTransitN (RTLT) and RossThick-Roujean (RTR). Then, the spectral reflectance of four typical military materials was measured using an imaging spectrometer, and the fitting effects of different models were evaluated. Experiments show that the three semi-empirical kernel-driven models have good data fitting ability for different types of military materials.Overall, RTLSR model has the best data fitting ability and the best stability of inversion results.
期刊介绍:
Rapid progress in optics and photonics has broadened its application enormously into many branches, including information and communication technology, security, sensing, bio- and medical sciences, healthcare and chemistry.
Recent achievements in other sciences have allowed continual discovery of new natural mysteries and formulation of challenging goals for optics that require further development of modern concepts and running fundamental research.
The Journal of the European Optical Society – Rapid Publications (JEOS:RP) aims to tackle all of the aforementioned points in the form of prompt, scientific, high-quality communications that report on the latest findings. It presents emerging technologies and outlining strategic goals in optics and photonics.
The journal covers both fundamental and applied topics, including but not limited to:
Classical and quantum optics
Light/matter interaction
Optical communication
Micro- and nanooptics
Nonlinear optical phenomena
Optical materials
Optical metrology
Optical spectroscopy
Colour research
Nano and metamaterials
Modern photonics technology
Optical engineering, design and instrumentation
Optical applications in bio-physics and medicine
Interdisciplinary fields using photonics, such as in energy, climate change and cultural heritage
The journal aims to provide readers with recent and important achievements in optics/photonics and, as its name suggests, it strives for the shortest possible publication time.