With the progress of long-wave infrared detector technology, space-based infrared remote sensing satellite technology has developed rapidly by selecting Aerospace large array long-wave infrared detector. The response of long-wave infrared detectors is strongly nonlinear, which leads to large correction errors in traditional non-uniformity correction algorithms based on linear models, thereby affecting the effectiveness of the satellite in orbit. Aiming at this problem, combing the statistical analysis results of a large number of laboratory data and satellites in orbit data, a new long-wave infrared detector nonlinear response model was established, and an new non-uniformity correction algorithm based on improved Gamma curve was proposed accordingly, which was in order to effectively overcome the influence of the strong nonlinear response of infrared detector on the correction accuracy. Firstly, the nonlinear response model based on improved Gamma curve for infrared detector was established, and the nonlinear compression mapping operation on the original image data was completed to achieve linearization of the infrared detector response. Secondly, the linearization algorithm was used to implement non-uniformity correction based on space-borne calibration technology. Meanwhile, the calibration temperature point was dynamically updated according to the established model parameters. Finally, the actual image after non-uniformity correction was restored by inverse nonlinear compression mapping. The experimental result based on artificial blackbody and on orbit real infrared images show that the proposed algorithm can effectively solve the influence of strong nonlinearity of infrared detector response on the correction accuracy, and the visual effect and quantitative index of the corrected image are better than the traditional space-borne non-uniformity correction algorithm.