To address the shortcomings of existing infrared image enhancement algorithms such as under enhancement,over enhancement and loss of small details,an infrared image enhancement algorithm based on low frequency redistribution and edge enhancement is proposed. The infrared image is decomposed into low frequency and high frequency images by Retinex based on improved guided filtering. In order to take full advantage of the dynamic space of pixel level,the low frequency image is uniformly redistributed to improve the brightness and clarity of the image；and the proposed directional gradient operator is used to extract the edge of the high frequency image,with which the edge of the high frequency image is enhanced,so as to further improve the contrast of the image. The enhanced infrared image is obtained by the Retinex inverse transformation of the enhanced low frequency and high frequency images. The experimental results show that compared with some existing methods,the information entropy and Brenner index of the enhanced image are higher,and the NIQE index is smaller,so the method is more effective in improving the contrast of infrared image and better enhancing the texture details of the image while maintaining the naturalness of the image.