POSE: Phase II: An Open Source Hyperspectral Imaging Ecosystem

传统摄影通过简单的色彩表现来产生供人类感知的图像。高光谱成像（HSI）将成像技术从人类感知的再现扩展到精确的光谱辐射记录，范围从紫外线到红外波长。HSI增强的识别能力被用于生物、医学、制药、材料、文化遗产保护和空间操作等领域的大量应用。然而，过去HSI的应用受到分散的知识产权、孤立和不成熟的软件工具和数据、陡峭的学习曲线以及缺乏行业标准的限制。该项目通过开发一个开源的恒生指数生态系统（HSI- ose）来释放恒生指数的潜力，该生态系统由恒生指数仪器制造商、学术研究人员、软件提供商和普通用户共同贡献。该项目的新颖之处在于为HSI-OSE建立了一个围绕工具和数据中心的可持续组织结构，该结构支持社区中注册用户的持续、开放和异步贡献。该项目的影响正在加速自然资源监测、气候变化评估、人工制品认证、癌症诊断、病原体检测以及药品和种子质量控制等应用领域的进展。HSI-OSE通过促进制造商、研究人员和用户之间的协同作用，通过工具和数据共享以及功能请求，推进了高光谱成像领域的知识。凭借HSI数据资源的中心枢纽，它可以通过机器学习（ML）和人工智能（AI）进一步应用该技术。在每次HSI记录会话中产生大量数据，描述成像主体的属性、特性或特征。需要复杂的软件工具来处理和解释这些数据。该项目创建了一个全面的HSI数据资源，并为软件开发开发了协议和标准，以实现跨许多机器ML/AI应用程序的数据共享。来自HSI- ose的文档完备的开源软件工具和硬件设计也为HSI技术的新采用者的进入提供了便利。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Traditional photography produces images for human perception with a simple representation of color. Hyperspectral Imaging (HSI) expands imaging beyond reproduction for human perception to precise spectral radiance recording ranging from the ultraviolet to the infrared wavelengths. The enhanced discernment enabled by HSI is used to benefit an abundance of applications across biology, medicine, pharmaceuticals, materials, cultural heritage preservation, and space operations. However, the application of HSI in the past has been inhibited by dispersed intellectual property, siloed and immature software tools and data, steep learning curves, and lack of industry standards. This project is releasing the potential of HSI by developing an open-source HSI ecosystem (HSI-OSE) with contributions from HSI instrument manufactures, academic researchers, software providers, and general users. The project’s novelties are a sustainable organizational structure for the HSI-OSE established around a tool and data hub that enables continuous, open, and asynchronous contributions from registered users in the community. The project's impacts are accelerating progress in application areas such as natural resource monitoring, climate change assessment, artifact authentication, cancer diagnostics, pathogen detection, and quality control in pharmaceuticals and seeds.The HSI-OSE advances knowledge in the field of hyperspectral imaging by promoting synergy among the community of manufacturers, researchers, and users with tools and data sharing, as well as feature requests. With a central hub for HSI data resources, it enables further applications of the technology through machine learning (ML) and artificial intelligence (AI). Large amounts of data are generated in each HSI recording session depicting the attributes, properties, or characteristics of the imaging subject. Sophisticated software tools are required to process and interpret these data. This project creates a comprehensive HSI data resource and develops the protocols and standards for software development to enable data sharing across many machine ML/AI applications. The well-documented open-source software tools and hardware designs from the HSI-OSE also facilitate the entry of new adopters of the HSI technology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.