The TRICLOBS Dynamic Multi-Band Image Data Set for the Development and Evaluation of Image Fusion Methods.

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.

Search performance with discrete-cell stimulus arrays: filtered naturalistic images and probabilistic markers.

In order to partially fill the gap between search studies with artificial and naturalistic stimuli, experiments with segmented and spatially filtered images of real stimuli in the discrete cells of search arrays were conducted. RT × set size functions obtained with the spatially filtered arrays were compared with those obtained with geometric and other types of arrays. With the aid of Fourier analysis, components of target certainty/uncertainty, target-distractor similarity/dissimilarity, and distractor homogeneity/heterogeneity were evaluated for their effects on search performance and efficiency. The comparative effects of valid/invalid and ambiguous/unambiguous markers of search items were included in the experiments to probe the potential contributions of top-down and bottom-up control to search with naturalistic stimuli. Visual coding in the form of spatial frequency passbands and top-down preferences for distractor search were used to explain the results.