Aiming at the problems of low contrast, unhighlighted detail information and poor overall sharpness of wide dynamic range infrared images in terms of visual effects, a wide dynamic range infrared image detail enhancement algorithm based on the guided filter layering is proposed in this paper. The original image is layered using variance decision weighted guided filtering to obtain a base layer closer to the original image and a finer detail layer. In order to upgrade the contrast of the base layer, the global clipping point of CLAHE are firstly improved to enhance the enhancement effect, and then the integration of global and local histograms is guided based on the AC visual salience model, giving reasonable consideration to the image background and target. Moreover, to enhance the detail information effectively, a new detail layer with more comprehensive information is obtained based on multi-scale weighted guided filtering, followed by noise cancellation using gradient domain guided filtering, and then the Sigmoid function is used to compress the strong edge and highlight the subtle target, and finally the information of the two layers is fused and output. The experimental results show that the proposed algorithm is stronger than the comparison algorithm in both subjective vision and quantitative indexes, and has strong adaptability and robustness.