On an adaptive scene-based gray super-resolution technique of infrared focal plane array imaging system

Abstract

When infrared focal plane array imaging system detects targets, especially small targets, there is the problem of low gray resolution. In this paper, an adaptive scene-based gray super-resolution technique is proposed, aiming to solve the problem. The paper gives a detailed description on the method of image gray super-resolution by adjusting the signal sample range in infrared focal plane array (IRFPA) imaging system. The method contains the following three parts: extracting the effective gray range from the scene, and obtaining the basis of super-resolution adjustment; providing the adjusting parameters after filter-predicting the basis of adjustment, combining with the adaptive LMS-based filtering algorithm; and completing gray super-resolution by controlling the parameters in super-resolution circuit. Finally, the total solution is experiment validated. The experiment in infrared focal plane array imaging system has proven the feasibility and effectiveness of this method, and the improvement of super-resolution. Then test set shows the MRTD can be increased more than one time.