计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (34): 196-198.

• 图形、图像、模式识别 • 上一篇    下一篇

改进的FKCN与局部信息相结合的图像分割

黄宁宁1,贾振红1,余银峰1,杨 杰2,庞韶宁3   

  1. 1.新疆大学 信息科学与工程学院,乌鲁木齐 830046
    2.上海交通大学 图像处理与模式识别研究所,上海 200240
    3.新西兰奥克兰理工大学 知识工程与开发研究所,新西兰 奥克兰 1020
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-12-01 发布日期:2011-12-01

Algorithm for remote sensing image segmentation based on combination of the improved FKCN and local information

HUANG Ningning1,JIA Zhenhong1,YU Yinfeng1,YANG Jie2,PANG Shaoning3   

  1. 1.College of Information Science and Engineering,Xinjiang University,Urumqi 830046,China
    2.Institute of Image Processing and Pattern Recognition,Shanghai Jiao Tong University,Shanghai 200240,China
    3.Knowledge Engineering and Discovery Research Institute,Auckland 1020,New Zealand
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-12-01 Published:2011-12-01

摘要: FKCN在分割图像时存在速度慢,对噪声比较敏感等问题。对FKCN进行改进,提出了快速的FKCN与图像局部信息相结合的遥感图像分割算法,将图像的空间信息和像素信息引入到改进的FKCN图像分割算法中,从而提高了FKCN的分割速度而且还增强了抗噪性能。实验结果表明,该算法显示了很好的分割效果和较强的抗噪性能。

关键词: Kohonen网络, 局部信息, 遥感图像分割, 模糊聚类

Abstract: Aiming at the problem that the conventional FKCN algorithm is noise sensitive and slow,an image segmentation method via the improved FKCN algorithm with spatial information is presented.The method combines the standard FKCN algorithm with spatial information and pixel information.The experimental results show that the proposed method can segment the image effectively,and properly and the new algorithm is shown to be effective in image segmentation and has good performance of resisting noise.

Key words: Kohonen network, local information, remote sensing image segmentation, fuzzy cluster