Thomas Jean-Baptiste, Lapray Pierre-Jean, Le Moan Steven
Imagerie et Vision Artificielle (ImViA) Laboratory, Department Informatique, Electronique, Mécanique (IEM), Université de Bourgogne Europe, 21000 Dijon, France.
Department of Computer Science, NTNU-Norwegian University of Science and Technology, 2815 Gjøvik, Norway.
Sensors (Basel). 2025 Jan 23;25(3):675. doi: 10.3390/s25030675.
Recent advances in spectral imaging have enabled snapshot acquisition, as a means to mitigate the impracticalities of spectral imaging, e.g., expert operators and cumbersome hardware. Snapshot spectral imaging, e.g., in technologies like spectral filter arrays, has also enabled higher temporal resolution at the expense of the spatio-spectral resolution, allowing for the observation of temporal events. Designing, realising, and deploying such technologies is yet challenging, particularly due to the lack of clear, user-meaningful quality criteria across diverse applications, sensor types, and workflows. Key research gaps include optimising raw image processing from snapshot spectral imagers and assessing spectral image and video quality in ways valuable to end-users, manufacturers, and developers. This paper identifies several challenges and current opportunities. It proposes considering them jointly and suggests creating a new unified snapshot spectral imaging paradigm that would combine new systems and standards, new algorithms, new cost functions, and quality indices.
光谱成像的最新进展实现了快照采集，以此作为减轻光谱成像不切实际之处的一种手段，例如对专业操作人员的需求以及笨重的硬件设备。快照光谱成像，如在光谱滤波器阵列等技术中，也以牺牲空间光谱分辨率为代价实现了更高的时间分辨率，从而能够观测时间事件。设计、实现和部署此类技术仍具有挑战性，特别是因为在不同的应用、传感器类型和工作流程中缺乏清晰的、对用户有意义的质量标准。关键的研究空白包括优化来自快照光谱成像仪的原始图像处理，以及以对终端用户、制造商和开发者有价值的方式评估光谱图像和视频质量。本文识别了若干挑战和当前的机遇。它提议综合考虑这些因素，并建议创建一种新的统一快照光谱成像范式，该范式将结合新的系统和标准、新算法、新成本函数以及质量指标。
