Wavelet transform is an effective method for infrared small target detection. The characteristics of signal and noise are different in different sub-bands and different directions,so the single threshold is often unable to get a satisfactory result. To solve this problem,an adaptive multi-mode infrared small target detection algorithm was presented based on wavelet transform. The algorithm can automatically adjust the threshold according to the distribution of noise in different scales and directions,which makes the detection results more effective. Adaptive Bayes shrink threshold and generalized cross validation threshold are used to deal with the wavelet coefficients of each sub-band,and then the wavelet images are reconstructed by the obtained coefficients. Finally,the infrared small target is gotten by one simple global threshold segmentation. The experimental results demonstrate that the proposed algorithm has better detection performance and robustness than the other method.