Thermal Infrared Colorization Using Deep Learning

Day by day the usage of infrared cameras has been increasing in the world. With the increasing use of thermal infrared cameras and images, especially in military, security and medicine, the need for coloring thermal infrared images to visible spectrum has arisen. In this study, a deep based model has been developed to generate visible spectrum images (RGB - Red Green Blue) from thermal infrared (TIR) images. In the proposed model, an autoencoder architecture with skip connections has been used to generate RGB images. KAIST-MS (Korea Advanced Institute of Science and Technology-Multispectral) dataset used for training and test the developed model. The experimental results extensively tested using Peak Signal-to-Noise Ratio (PSNR), Least Absolute Deviations (L1), Root Mean Squared Error (RMSE) and Structural Similarity Index Measure (SSIM).