New retinex model-based infrared image enhancement

The thermal imaging system often suffers from low contrast, low-spatial resolution, and blur under heat radiation conditions. Currently, available image enhancement methods are most suitable for visible images. However, existing methods often enhance objects and noise for noisy infrared images, simultaneously producing a very poor result. This paper presents two single infrared image enhancement methods, including (i) a bi-logarithmic histogram equalization with Quasi-symmetric correction and (ii) a combined luminance and reflection decomposition and image fusion-based method. Computer simulations on benchmarking infrared Kuangxd database show that the proposed algorithm performance outperforms conventional image enhancement methods, including a cutting-edge learning-based method, in terms of subjective and objective evaluations.