Improved Object Detection in Thermal Imaging Through Context Enhancement and Information Fusion: A Case Study in Autonomous Driving
Junchi Bin · Ran Zhang · Shan Du · Erik Blasch · Zheng Liu
Abstract
With advances sensory technologies, autonomous driving systems incorporate more imaging sensors such as thermal cameras to enhance the capability of environmental perception beyond the visible spectrum. This paper proposes an integrated context enhancement and information fusion framework (CEIFF) to generate enhanced colorized synthetic visible (SVI) images from thermal images. And, the SVI and thermal images are fused for improved perception quality. The case study shows the effectiveness of the proposed CEIFF on a multimodal autonomous dataset.
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