To solve the problems of high dynamic range, low image contrast and blurred edges of original infrared images, an infrared image detail enhancement algorithm based on adaptive guided filtering is proposed. Firstly, the input image is divided into a base layer and a detail layer using the designed parameter-adaptive guided filtering. Then, the plateau histogram equalization is used to compress the dynamic range of the base layer, and mask weighting and gamma transform are used to suppress detail layer noise and enhance the image details. Finally, the processed base and detail layers are linearly weighted and stretched to the display range. The experiment results show that compared with the traditional and advanced infrared image detail enhancement algorithms, the proposed algorithm has stronger scene adaptability, and has obtained better enhancement effects in scenes such as high dynamic range scene, complex outdoor, and sea and sky. Compared with the advanced algorithm, the proposed algorithm has an average improvement of 35.3% in the average gradient and an average of 10.7% in the perception-based image quality evaluator. The proposed algorithm can effectively compresses the dynamic range of infrared images, significantly improves image contrast and sharpness, and the processing results are more helpful for human eyes to observe.