مورد إلكتروني
Active and Low-Cost Hyperspectral Imaging for the Spectral Analysis of a Low-Light Environment.
| العنوان: | Active and Low-Cost Hyperspectral Imaging for the Spectral Analysis of a Low-Light Environment. |
|---|---|
| المؤلفون: | Tang, Yang |
| المصدر: | Sensors (Basel, Switzerland); vol 23, iss 3, 1437; 1424-8220 |
| بيانات النشر: | eScholarship, University of California 2023-01-01 |
| تفاصيل مُضافة: | Tang, Yang Song, Shuang Gui, Shengxi Chao, Weilun Cheng, Chinmin Qin, Rongjun |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Hyperspectral imaging is capable of capturing information beyond conventional RGB cameras; therefore, several applications of this have been found, such as material identification and spectral analysis. However, similar to many camera systems, most of the existing hyperspectral cameras are still passive imaging systems. Such systems require an external light source to illuminate the objects, to capture the spectral intensity. As a result, the collected images highly depend on the environment lighting and the imaging system cannot function in a dark or low-light environment. This work develops a prototype system for active hyperspectral imaging, which actively emits diverse single-wavelength light rays at a specific frequency when imaging. This concept has several advantages: first, using the controlled lighting, the magnitude of the individual bands is more standardized to extract reflectance information; second, the system is capable of focusing on the desired spectral range by adjusting the number and type of LEDs; third, an active system could be mechanically easier to manufacture, since it does not require complex band filters as used in passive systems. Three lab experiments show that such a design is feasible and could yield informative hyperspectral images in low light or dark environments: (1) spectral analysis: this system's hyperspectral images improve food ripening and stone type discernibility over RGB images; (2) interpretability: this system's hyperspectral images improve machine learning accuracy. Therefore, it can potentially benefit the academic and industry segments, such as geochemistry, earth science, subsurface energy, and mining. |
| مصطلحات الفهرس: | active hyperspectral imaging, sensing, spectrum-based recognition, Analytical Chemistry, Environmental Science and Management, Ecology, Distributed Computing, Electrical and Electronic Engineering, article |
| URL: | |
| الإتاحة: | Open access content. Open access content public |
| ملاحظة: | application/pdf Sensors (Basel, Switzerland) vol 23, iss 3, 1437 1424-8220 |
| أرقام أخرى: | CDLER oai:escholarship.org:ark:/13030/qt0rn0h295 qt0rn0h295 https://escholarship.org/uc/item/0rn0h295Test https://escholarship.orgTest/ 1391576146 |
| المصدر المساهم: | UC MASS DIGITIZATION From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1391576146 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |