How to compress the High Dynamic Range (HDR) data collected by the infrared detector into the observable low-dynamic-range image with outstanding details,high contrast and low background noise while retaining the original image information as much as possible has always been a difficult aspect of infrared technology.In order to solve this problem,an infrared image enhancement mapping method based on the fusion of multi-scale multi-histogram mapping results is proposed.Firstly,the global linear transform and the multi-scale window CLAHE are used to map the HDR infrared image separately,and then adaptive weight calculation is conducted based on local saliency and dynamic-range features,and the multi-histogram mapping results are fused to solve the scene adaptability problem.At the same time,the fusion weight is optimized by using guided filtering in the weight calculation,and finally the adaptive detail enhancement is realized by using the Gaussian kernel function in the gray domain.The experimental results show that,compared with other methods,the proposed method can effectively enhance the image contrast,enrich the image details and reduce the background noise,and has strong scene adaptability.