Toet Alexander
TNO, Kampweg 5, 3769DE Soesterberg, The Netherlands.
Data Brief. 2017 Sep 22;15:249-251. doi: 10.1016/j.dib.2017.09.038. eCollection 2017 Dec.
Despite of the ongoing interest in the fusion of multi-band images for surveillance applications and a steady stream of publications in this area, there is only a very small number of static registered multi-band test images (and a total lack of dynamic image sequences) publicly available for the development and evaluation of image fusion algorithms. To fill this gap, the TNO Multiband Image Collection provides intensified visual (390-700 nm), near-infrared (700-1000 nm), and longwave infrared (8-12 µm) nighttime imagery of different military and surveillance scenarios, showing different objects and targets (e.g., people, vehicles) in a range of different (e.g., rural, urban) backgrounds. The dataset will be useful for the development of static and dynamic image fusion algorithms, color fusion algorithms, multispectral target detection and recognition algorithms, and dim target detection algorithms.
尽管对于用于监视应用的多波段图像融合一直存在兴趣，并且该领域也有源源不断的出版物，但公开可用的用于图像融合算法开发和评估的静态配准多波段测试图像数量极少（并且完全缺乏动态图像序列）。为了填补这一空白，TNO多波段图像集提供了不同军事和监视场景下的增强视觉（390 - 700纳米）、近红外（700 - 1000纳米）和长波红外（8 - 12微米）夜间图像，展示了一系列不同（如农村、城市）背景中的不同物体和目标（如人员、车辆）。该数据集将有助于开发静态和动态图像融合算法、颜色融合算法、多光谱目标检测与识别算法以及暗目标检测算法。
