Dual-tree complex wavelet transform(DT-CWT) is an effective image processing method,but when it is directly applied to infrared small target detection,it is particularly sensitive to high-frequency information in the image,and it is impossible to effectively filter out the noise while retaining the target.The paper makes full use of the advantages of dual-tree complex wavelet method,and proposes an infrared small target detection algorithm based on DT-CWT and image entropy for the high-frequency sensitive problem,which can effectively remove clutter in the image and highlight the small target.The method firstly performs DT-CWT decomposition on the original image,sets its low-frequency sub-band to zero,and the high-pass subbands are reconstructed by DT-CWT.Then the reconstructed image is decomposed by DT-CWT again,and the decomposed low-pass subbands are filtered by improved Top-Hat operator,while retaining the decomposed sub-bands in the ±15° direction,and processing them by high-pass filtering;after that,the filtered low-frequency sub-bands are processed.The difference between the image and the original low-frequency sub-band image is obtained,and the low-frequency difference image is obtained.Finally,The differential low-pass image and the filtered high-pass subbands image are reconstructed by DT-CWT.The small infrared targets are extracted by weighting the local image entropy.The experimental results show that the proposed algorithm is superior to the contrast algorithm in BSF and SCRG,and can effectively suppress the clutter in the background and improve the signal-to-clutter ratio of infrared small target image.