We discuss the fusion of far infrared (FIR) and near infrared(NIR) image data for an improved automotive night vision device. The twowavebands have differing characteristics when using cameras sensitive tothese wavelengths in the automotive environment. It is the aim of ourwork to fuse the information from these two sensor types to optimize thebenefits of both wavebands. The choice of NIR radiation for anautomotive night vision system with active illumination has beendetermined by one automotive manufacturer as the most suitable wavebandfor a single sensor night vision device. FIR radiation was chosen as asecond waveband for fusion because sensors operating at thesewavelengths detect passive radiation from objects at temperatures ofapproximately 300 K. Therefore, in principle, it should be possible toimage to the horizon on a dry and humidity free night, and to provideclear images of hot bodies such as pedestrians and vehicles in use. Wehave chosen pyramid based techniques to fuse the two image types as theyallow maximum flexibility, are relatively simple, and computationallyefficient. We have adapted pyramid methods to suit our requirements. Wedemonstrate improved fusion for our particular application
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