Improved algorithm for infrared non-uniform correction

In recent years, infrared imaging technology is widely used in various fields such as national security and night vision assistance. Due to the limitations of the fabrication materials of Infrared Focal Plane Array and their processes, it inevitably results in non-uniformity on the image, which makes the necessary detail information submerged in the noise, thus affecting the visual observation, and thus the need for non-uniformity correction processing of infrared images. In order to further improve the Non-uniformity Correction (NUC) effect of uncooled infrared detectors, a calibration-based non-uniformity correction algorithm is improved in this paper. This algorithm is based on single-point calibration and two-point calibration Non-uniformity Correction methods, which not only implements the consistency advantage of two-point calibration gain correction coefficients, but also combines the stability of single-point calibration bias correction coefficients, so as to obtain a better correction effect. In order to evaluate the correction effect of the algorithm, the research object of this paper is an uncooled long-wave infrared detector with a size of 384 pixel×288 pixel, and the improved algorithm is examined using an infrared imaging system. The experimental data show that compared with the single-point correction and two-point correction, the correction algorithm in this paper can more effectively reduce the non-uniformity of the image. Overall, the correction effect of this paper's algorithm is better and more accurate.