中文摘要：

针对现有阈值分割法通常只考虑图像直方图的统计信息，而忽略了图像目标和背景类内灰度分布的均匀性，提出指数灰度熵分割算法，并推广得到三维指数灰度熵分割算法。给出了一维指数灰度熵阈值法及三维指数灰度熵阈值法的原理，在三维直方图上，将降维处理和优化搜索策略相结合，得到最优分割阈值。理论证明，阈值搜索复杂度由原来的O（L3）降至O（L1／2）。实验结果表明，与现有的多种阂值法相比，所提算法抗噪性能更强、分割效果更优，且运算时间大为减少。

英文摘要：

In view of the existing threshold segmentation methods which usually only consider the statistical information from image histogram, while ignoring the gray distribution uniformity of the image target class and the background class, one-dimensional exponential gray entropy segmentation algorithm is put forward and three-dimensional exponential gray entropy segmentation algorithm is deduced. The principles of one-dimensional exponential gray entropy algorithm and three-dimensional exponential gray entropy algorithm are presented. The optimum segmentation threshold is got by combining dimension reduction and optimal search strategy on the three-dimensional histogram. The search complexity is reduced from O（L3） to O（L1/2） in theory. Experimental results show that, compared with other existing threshold algorithms, the proposed algorithm has better anti-noise performance, segmentation effect and its operation time is reduced greatly.