In this paper,a binocular heterogeneous imaging system with simple structure and high real time characteristics is built by combining infrared camera and RGB camera in order to solve the problems of unsatisfactory imaging effect of infrared image and visible image in night vision environment.Firstly,the infrared and visible images are acquired in real time using a dual threaded approach,and an entropy based adaptive h solving method is proposed for Non Local Mean filtering,which is capable of better eliminating the noise of infrared images.Then,the feature points of infrared and visible images are matched,and a slope consistency based method is introduced for image alignment,and finally images are fused by combining the Two scale Image Fusion(TIF)algorithm using improved base image fusion rules and multiple fusion algorithms to obtain the Infrared Radiation and RGB(IR RGB)fusion image with obvious targets,rich information and true to color.The TIF algorithm can efficiently and rapidly fuse infrared images with visible images,preserving the true color information characteristics of visible images for the surrounding environment while retaining the temperature extraction characteristics of infrared images.According to the data analysis,the entropy value of the IR RGB images of the TIF algorithm is improved by about 5.14%；their edge intensity all reach a maximum of 39.991,22.433,52.880.Compared with the common pixel level fusion methods,the speed of the proposed method is improved by an order of magnitude of 10 times.The research is of great importance in practical applications such as target identification and monitoring by means of real time imaging of infrared and visible light in a night vision environment.