中文摘要：

一个不规则的分割的区域编码算法基于脉搏，联合神经网络(PCNN ) 被介绍。PCNN 有联合脉搏、可变的阀值，有近似灰色的价值的这些邻近的象素能同时通过被激活的性质。一个人能得出 PCNN 有的优点认识到地区性的分割，和细节的一个结论原来的图象能被分割图象的参数调整完成，并且同时，小分割的区域能被避免。为不规则的分割的区域的更好的近似， Gram-Schmidt 方法，一组 orthonormal 基底函数被从一组线性独立的起始的底构造工作，被采用。因为重建的 orthonormal 方法，重构图象的质量能极大地被改进，进步图象传输将也是可能的。

英文摘要：

An irregular segmented region coding algorithm based on pulse coupled neural network（PCNN） is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approximate gray values can be activated simultaneously. One can draw a conclusion that PCNN has the advantage of realizing the regional segmentation, and the details of original image can be achieved by the parameter adjustment of segmented images, and at the same time, the trivial segmented regions can be avoided. For the better approximation of irregular segmented regions, the Gram-Schmidt method, by which a group of orthonormal basis functions is constructed from a group of linear independent initial base functions, is adopted. Because of the orthonormal reconstructing method, the quality of reconstructed image can be greatly improved and the progressive image transmission will also be possible.