Toet Alexander, Hogervorst Maarten A, Pinkus Alan R
TNO, Soesterberg, The Netherlands.
Air Force Research Laboratory, Wright-Patterson AFB, Ohio, United States of America.
PLoS One. 2016 Dec 30;11(12):e0165016. doi: 10.1371/journal.pone.0165016. eCollection 2016.
The fusion and enhancement of multiband nighttime imagery for surveillance and navigation has been the subject of extensive research for over two decades. Despite the ongoing efforts in this area there is still only a small number of static multiband test images available for the development and evaluation of new image fusion and enhancement methods. Moreover, dynamic multiband imagery is also currently lacking. To fill this gap we present the TRICLOBS dynamic multi-band image data set containing sixteen registered visual (0.4-0.7μm), near-infrared (NIR, 0.7-1.0μm) and long-wave infrared (LWIR, 8-14μm) motion sequences. They represent different military and civilian surveillance scenarios registered in three different scenes. Scenes include (military and civilian) people that are stationary, walking or running, or carrying various objects. Vehicles, foliage, and buildings or other man-made structures are also included in the scenes. This data set is primarily intended for the development and evaluation of image fusion, enhancement and color mapping algorithms for short-range surveillance applications. The imagery was collected during several field trials with our newly developed TRICLOBS (TRI-band Color Low-light OBServation) all-day all-weather surveillance system. This system registers a scene in the Visual, NIR and LWIR part of the electromagnetic spectrum using three optically aligned sensors (two digital image intensifiers and an uncooled long-wave infrared microbolometer). The three sensor signals are mapped to three individual RGB color channels, digitized, and stored as uncompressed RGB (false) color frames. The TRICLOBS data set enables the development and evaluation of (both static and dynamic) image fusion, enhancement and color mapping algorithms. To allow the development of realistic color remapping procedures, the data set also contains color photographs of each of the three scenes. The color statistics derived from these photographs can be used to define color mappings that give the multi-band imagery a realistic color appearance.
二十多年来,用于监视和导航的多波段夜间图像融合与增强一直是广泛研究的主题。尽管该领域一直在努力,但目前仍只有少量静态多波段测试图像可用于开发和评估新的图像融合与增强方法。此外,动态多波段图像目前也很缺乏。为了填补这一空白,我们展示了TRICLOBS动态多波段图像数据集,其中包含16个已配准的视觉(0.4 - 0.7μm)、近红外(NIR,0.7 - 1.0μm)和长波红外(LWIR,8 - 14μm)运动序列。它们代表了在三个不同场景中记录的不同军事和民用监视场景。场景包括静止、行走或奔跑的(军事和民用)人员,或携带各种物品的人员。车辆、树叶以及建筑物或其他人造结构也包含在场景中。该数据集主要用于开发和评估用于短程监视应用的图像融合、增强和色彩映射算法。这些图像是在使用我们新开发的TRICLOBS(三波段彩色微光观察)全天候监视系统进行的几次现场试验中收集的。该系统使用三个光学对准的传感器(两个数字图像增强器和一个非制冷长波红外微测辐射热计)在电磁频谱的视觉、近红外和长波红外部分记录一个场景。三个传感器信号被映射到三个单独的RGB颜色通道,数字化并存储为未压缩的RGB(伪)彩色帧。TRICLOBS数据集能够开发和评估(静态和动态)图像融合、增强和色彩映射算法。为了允许开发逼真的色彩重映射程序,该数据集还包含三个场景中每个场景的彩色照片。从这些照片中得出的颜色统计数据可用于定义色彩映射,使多波段图像具有逼真的颜色外观。