Segmenting satellite remote sensing cloud images is an essential step of analyzing satellite cloud image data. In order to segment satellite remote sensing cloud images more accurately, a satellite remote sensing cloud image segmentation method based on Chan Vese (CV) model incorporating edge information is proposed. Satellite cloud image is diffused and a smooth image is obtained. The edge information is calculated based on the smooth image. The edge information is incorporated into the CV model, and a distance regularized term is added to avoid the reinitialization of the level set function during its evolution. Experimental results show that, compared with conventional CV model, region-scalable fitting energy level set model and bias field correction level set model, the proposed method can segment region of cloud more accurately and the speed is faster.