Aiming at the detection problem for dim target in infrared image that contains background interference and noise, a detection method for dim target is proposed based on nonsubsampled contourlet transform (NSCT) and independent component analysis (ICA). Firstly, the background image separated from the original image by fast independent component analysis is subtracted from the original image. The residual image is denoised based on nonsubsampled contourlet transform and the new Top-hat transform is used as a filter, thus the preprocessed image is obtained. Then, the preprocessed image is segmented by the threshold selection algorithm based on the within-class variance and area difference between background and target. Lots of experiments are done with infrared images including small targets and a comparison is made with the detection methods of infrared target based on fast independent component analysis and nonsubsampled contourlet transform. The experimental results show that the suggested method is stronger in anti-noise performance and more superior in detection performance.