【摘要】 本文提出了一种新的灰度图象分割方法．该方法模拟了人类视觉由粗到细的分割过程，针对图象中各位置的不同内容采用不同的细节分辨率，形成多层感知的塔式结构；而在每一分辨率层上，采用小生境的遗传算法进行图象分割，使整个算法具有较强的鲁棒性、适用性、非监督性及高度的并行性，通过与单层遗传分割算法［1］相对比，显示了该方法具有更好的分割效果．更多还原

【Abstract】 To our best knowledge,classical image segmentation methods are serial in essence,with poorrobustness and limited application field. Genetic image segmentation algorithm was proposed in recent years,which can overcome those drawbacks in certain extent,but with single resolution, regions with different extent of details can not achieve good segmentation results simultaneously. We propose in this paper a new image segmentation method to solve this problem. It is based on multiresolution concept with multilayer structure. On each layer,genetic method is used to achieve segmentation result. Then from coarse to fine,the finalresult can be obtained. The whole process is proved to be robust and parallel. Compared with genetic segmentation method with single resolution, it can achieve better results.更多还原