Computational methods for improving thermal imaging for consumer devices

In consumer imaging, the spatial resolution of thermal microbolometer arrays is limited by the large physical size of the individual detector elements. This also limits the number of pixels per image. If thermal sensors are to find a place in consumer imaging, as the newly released FLIR One would suggest, this resolution issue must be addressed. Our work focuses on improving the output quality of low resolution thermal cameras through computational means. The method we propose utilises sub-pixel shifts and temporal variations in the scene, using information from thermal and visible channels. Results from simulations and lab experiments are presented.