According to infrared image characteristics, an infrared image segmentation method for improved Chan-Vese model based on wavelet multisale transform is presented. First, edge information is extracted by using wavelet multiscale transform, and it is added into energy function of Chan-Vese model to improve local control ability. Furthermore, internal energy term is added, which constraints level set function to approach signed distance function so as to avoid reinitialization of level set function. Then, wavelet low frequency subbands are segmented with improved Chan-Vese model from top to bottom, and segmented results are interpolated into next subbands as initiative contours. Finally, the method can realize infrared image segmentation. Experiments show that the method is very efficient and robust to noise.