Two-Dimensional Calibration for Fixed-Pattern Noise Reduction of Thermal Images

A two-dimensional calibration technique is proposed to reduce fixed-pattern noise in infrared thermal images for extending dynamic range of sampling integration time. Traditional two-point calibration generates correction coefficients by irradiance of two reference temperatures, providing excellent spatial noise performance for the predetermined sampling integration time. To break the limitation of invariable integration time, two-dimensional calibration is proposed, which generates correction coefficients not only under irradiance of two temperatures, but also with two integration times. By exploring information from both temperature and integration, the new approach can reduce fixed-pattern noise for different sampling integration time, requiring same computation complexity and hardware consumption as conventional two-point calibration. In experiments with infrared camera, the proposed method suppresses fixed-pattern noise to a low level with same correction coefficients for sampling integration time changing from 0.4 ms to 1.6 ms. Compared to traditional calibration-based approaches, the presented scheme extends dynamic range of integration time by four times.