Real-time scene-based nonuniformity correction using feature pattern matching

Infrared cameras require constant nonuniformity correction because image nonuniformity occurs with environmental changes. In this paper, we propose a nonuniformity correction algorithm using feature pattern matching that can correct nonuniformities in real time. The proposed algorithm consists of motion estimation and nonuniformity correction steps. The motion estimation algorithm consists of feature extraction, feature point simplification, and feature point pattern generation steps and is proposed to calculate the amount of motion between frames in real time using a field programmable gate array. The experimental results confirm that the proposed method is robust against ghost phenomenon, compared to a statistics-based nonuniformity correction, and improves the real-time performance while providing the same performance as the existing interframe registration-based nonuniformity correction algorithm.