Abstract:This paper solves the image segmentation problem by using the quantum multi-threshold maximum entropy algorithm.Firstly we determine the image maximum entropy probability density function,calculate the maximum entropy density before test,then the image gray value is divided into two regions of the background and the object,the pixel quantum bit values in different gray levels are counted,the optimal segmentation threshold is obtained according to the proportion of pixels.Finally the algorithm steps are proposed.Experimental simulation shows that the algorithm has a stronger capability at noise suppressing,has a higher accuracy while preserving the edge information.