Infrared Image Brightness Correction for TIR Object Tracking
Xiaosong Wang, Haiying Wang, Chao Tian · 2021 7th International Conference on Computer and Communications (ICCC) · 2021
Thermal imaging has been widely used in numerous applications of computer vision. However, in infrared videos, drastic change to bright or dark is a common phenomenon. 8bit thermal image suddenly turning bright or dark mainly caused by two reasons: change in light and dark pixel values distribution and the temperature change inside the infrared camera during photography. As a result, both the tracking performance and the visual effect are affected. To this end, we analyzed the problem from the principle of infrared imaging. We proposed a brightness correction algorithm based on the Kalman filter, which suppressed adjacent frames’ brightness flickers, thus improving both tracking performance and visual effect. Experiments on a standard tracking benchmark LSOTB-TIR demonstrate that our algorithm achieves better tracking performance on flickering sequences while not negatively influencing regular infrared videos.