Image processing is an important way to obtain information and is widely used in important fields such as military, medical and transportation fields. Image segmentation plays an important role in image processing. Aiming at the uncertainty in the process of image segmentation, and in order to obtain more accurate image segmentation results, we proposes a singlethreshold image segmentation algorithm based on variable precision least square rough entropy and particle swarm optimization. It uses the variable precision rough set to represent the image, utilizes the variable precision least square rough entropy to solve the optimal segmentation threshold, and employs the particle swarm optimization to improve segmentation efficiency. Experimental results show that the singlethreshold segmentation algorithm is superior to the maximum average entropy method, and demonstrates that variable precision rough entropy can settle the uncertainty problem in image segmentation process.