为了提高地面和云层等红外复杂背景下弱小目标的检测性能，提出了一种基于视觉细胞响应模型的红外弱小目标背景抑制新方法.首先利用简单细胞的感受野计算模型将原始图像采用Gabor函数卷积获得相同大小的两幅图像;然后采用设计的复杂细胞响应的非线性汇聚策略函数对获得的两幅图像进行融合处理，从而将红外图像中弱小目标和背景杂波分离，达到抑制背景的目的;最后采用自适应阈值分割技术得到目标点，实现了对红外弱小目标的检测跟踪.实验结果显示，与去局部均值和最大中值滤波两种滤波方法相比较，该方法能有效地检测出信杂比较低的弱小目标信号.

To improve detection performance for weak and small targets signal in complex infrared background, such as the ground and the cloud, a dim and small target background suppression method is presented based on vision cell response model was presented. Firstly, according to simple cell receptive field model, original infrared image is decomposed to two images with different Gabor functions using convolution. And then, the function of nonlinear convergence of complex cell response is used to fusion two images obtained for separation small target with background clutter in infrared image. Finally, target image is obtained by using classical adaptive thresholding method. Several groups of experimental results demonstrate that the proposed method can segment the infrared target image effectively, compared with several classical infrared dim and small target background suppression methods, such as local means remove and max median filter methods.