The image details are blurred,the details in the dark areas are lost,and the contrast becomes low during the high dynamic infrared images compression.To solve the above mentioned problems,an infrared image details adaptive enhancement algorithm based on guided filtering layering is proposed.The histogram equalization method with optimized penalty term is used for the background compression,and the combination of impulse noise multi-scale detection and Weber′s theorem is adopted to solve the dark areas detail loss and the blurring of weak detail.Compared with the traditional enhancement algorithms based on layered idea,mapping,Retinex and integrated learning,the integrated main and objective experimental results show that the proposed algorithm has good effects in background layer contrast and illumination intensity optimization,detail layer noise suppression and weak detail enhancement.The proposed algorithm provides the optimistic results in terms of information entropy,PSNR and SSIM.And the processing speed reaches 150 frames per second.The proposed algorithm not only improves the overall contrast of the image,but also highlights the local details of the image.It is suitable for the wide temperature application under complex environments.