Low-cost, low-resolution IR system with super-resolution interpolation of thermal images for industrial applications

In this paper authors present application of deep neural networks for super-resolution interpolation of infrared images. A residual neural network with reduced number of layers was used. The transfer learning using RGB visual images was applied in this research. The validation of the network was performed for 32×24 and 160×120 pixels infrared images, with the up-sampling scale factors 2, 3, 4, 5 and 6. Monitoring of high temperature industrial processes like inductive heating and thermal hardening is the main application of proposed methods.