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Far/near infrared adapted pyramid-based fusion for automotive night vision

机译:远/近红外适应的汽车夜视基于金字塔的融合

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We discuss the fusion of far infrared (FIR) and near infrared (NIR) image data for an improved automotive night vision device. The two wavebands have differing characteristics when using cameras sensitive to these wavelengths in the automotive environment. It is the aim of our work to fuse the information from these two sensor types to optimize the benefits of both wavebands. The choice of NIR radiation for an automotive night vision system with active illumination has been determined by one automotive manufacturer as the most suitable waveband for a single sensor night vision device. FIR radiation was chosen as a second waveband for fusion because sensors operating at these wavelengths detect passive radiation from objects at temperatures of approximately 300 K. Therefore, in principle, it should be possible to image to the horizon on a dry and humidity free night, and to provide clear images of hot bodies such as pedestrians and vehicles in use. We have chosen pyramid based techniques to fuse the two image types as they allow maximum flexibility, are relatively simple, and computationally efficient. We have adapted pyramid methods to suit our requirements. We demonstrate improved fusion for our particular application.
机译:我们讨论了用于改进的汽车夜视设备的远红外(FIR)和近红外(NIR)图像数据的融合。当使用对汽车环境中这些波长的相机敏感时,两个波段具有不同的特性。我们的工作旨在融合来自这两个传感器类型的信息,以优化两个波段的好处。具有积极照明的汽车夜视系统的NIR辐射的选择已经由一个汽车制造商确定为单个传感器夜视装置的最合适的波段。选择FIR辐射作为第二波段进行融合,因为在这些波长下操作的传感器检测到从大约300k的温度的物体中检测被动辐射。因此,原则上,应该可以在干燥和湿度自由夜间图像到地平线图像。并提供清晰的热身图像,如行人和​​车辆。我们选择了基于金字塔的技术来融合了两种图像类型,因为它们允许最大的灵活性,是相对简单的,并且计算效率。我们有适应金字塔的方法,以满足我们的要求。我们展示了对我们特定应用的改进融合。

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