An infrared non-uniformity correction algorithm based on zereo virtual perimeter diaphragm strips for robot vision imaging

In allusion to infrared non-uniformity noise of robot vision imaging, an infrared non-uniformity correction algorithm based on zereo virtual perimeter diaphragm strips is proposed, which does not need any prior information. This algorithm initially executes one-point correction to the perimeter detectors using zero virtual perimeter diaphragm strips. Then based on the scene information and shift between adjacent frames, a special algebraic algorithm is proposed to transport correction parameters from perimeter detectors to those interior un-corrected ones. In this way, the correction parameters of the whole field of view (FOV) are calculated, and the infrared vision imaging quality is improved. Theory analysis and simulation prove that this algorithm is feasible and effective. It proves to get a satisfying correction effect after being tested by simulated infrared images, and this algorithm is feasible and effective.