Gradient sky scene based nonuniformity correction and local weighted filter based denoising

The nonuniformity of infrared focal plane array (IRFPA) seriously affects the image quality and the measurement accuracy of the infrared detector system. Long-wave infrared (LWIR) detector has highly sensitivity and image unstable factors, and the nonuniformity tends to drift slowly with the change of the environment. In this paper, we propose a new nonuniformity correction (NUC) algorithm based on gradient sky scene. Firstly, we obtain the two-point calibration images at two different pitch angles in the pure sky without any cloud. And then, the gain and offset coefficients are calculated from the standard two-point NUC. Finally, the local weighted filter based denoising algorithm is employed to eliminate a few residual isolated noise. Computational result shows that the SNR gain of the proposed method is increased 2.50 dB compared to the standard two-point method based on uniform blackbody. Results indicate that the proposed algorithm exhibits a superior correction effect and has the advantage of low complexity which meets the real-time requirements.