Pixel-Level Fusion of Active/Passive Data for Real-Time Composite Feature Extraction and Visualization

摘要

A system has been developed whereby active LADAR and passive imaging data are registered in hardware at the pixel level. For the sake of discussion, the sensor is herein called a LADAR/EO pixel-level Fusion Sensor or LEFS. This sensor produces structural and spectral data embodied in one dataset, permitting composite feature extraction and visualization. The combined use of LADAR and passive EO/IR data has well known synergism. Our system fuses these two data types in a novel way such that real-time performance is possible. This significantly enhances the ability to quickly and correctly identify targets. By fusing the range data from the active sensor with the pixel-registered imagery, registered 3D images are available in real time (Figure 1). Each pixel is coded with full spectral information combined with structural information obtained by the active system (Figure 2). The resulting fully aligned high- dimension feature vector enhances target recognition and permits dense point matching for precise image mosaicking. A significant benefit is in combining the ability of pencil beam active systems to work at long ranges and to penetrate obscurants with the passive array s wide instantaneous field of view at increased resolution. One application in which this has had enormous benefit is in observation through partial or intermittent obscuration; e.g. with partial cloud cover or foliage. Reflected radiation associated with features within gaps in the obscuration are sensed passively while at the same time the active pencil beam efficiently maps structure within the revealed region (Figure 3). Pixel-level registration of data permits extended regions to be mapped by combining temporally or spatially diverse collections (Figure 4).