Thermal Image Enhancement through the Deconvolution Methods for Low-Cost Infrared Cameras.

An infrared (IR) thermal camera may provide a tool for real-time temperature monitoring for precise disease treatment using heat generated by light-induced photosensitisers, i.e. photothermal/ablation therapies. In this work, we quantitatively demonstrated that the spatial resolution of a low-cost low-resolution IR camera could be improved via two deconvolution methods. The camera point spread function was modelled experimentally and used to develop the deconvolution methods: (1) Richardson-Lucy blind deconvolution (BD); and (2) total variation constrained deconvolution (TD). The experimental results showed the improved spatial resolution (at 50% modulation transfer function: from the original 1.1 to 2.6 cycles/mm for the BD method and to 4.8 cycles/mm for the TD method) as well as contrast-to-noise ratio. With a properly chosen parameter, the TD method can resolve 1-mm size objects with the accurate temperature reading. The thermal image from the low-resolution IR camera enhanced by the TD method is comparable to that from a high-resolution IR camera. These results show that the TD method provides an effective way to improve the thermal image quality from a low-cost IR camera to monitor temperature of an object of 1-mm size, which meets the needed precision for advanced laser scanning protocols in photothermal/ablation therapies.