New scene-based nonuniformity correction algorithm based onGaussian mixture model

A new self-adaptive calibration algorithm for infrared images based on Gaussian mixed model (GMM) was put forward according to traditional temporal highpass filter (THPF). GMM is applied in the new algorithm for background modeling, and only the pixels whose output values satisfy certain conditions can be updated to the correction coefficient, and the background is updated selectively so as to avoid the influence of the foreground target on the update of the background. The performance of the proposed algorithm was evaluated through infrared image sequences with simulated and real fixed-pattern noise, and the simulated sequences quantitative evaluation was carried out by using the peak signal noise ratio (PSNR). Results show that the PSNR of the new algorithm increases by about 9 dB compared with the THPF. The subjective qualitative evaluation was adopted for real images, the correction results in the traditional method show obvious ghosting artifact while the results of the new algorithm are in the absence of ghosting artifact.