Infrared Complex Background Suppression Based on Vision Perception Model

To improve the detection performance for weak and small targets signal in complex infrared background, such as the ground and the cloud, the small target background suppression algorithm based on vision perception model (VPM) is presented. Firstly, with simple cell receptive field model, original infrared image is decomposed to two images by different Gabor functions using convolution. And then, the nonlinear convergence function of complex cell response is utilized to fusion two images obtained by separation small target with background clutter in infrared image. Finally, the target image is obtained by using classical adaptive threshold method. Several groups of experimental results demonstrate that the proposed method can suppress the infrared background effectively, compared with several classical infrared dim and small target background suppression methods, such as local means remove and two-dimensional least means square filter methods.