计算机科学 ›› 2019, Vol. 46 ›› Issue (11): 277-283.doi: 10.11896/jsjkx.181001985

• 图形图像与模式识别 • 上一篇    下一篇

高分影像复杂背景下的城市水体自动提取方法

王卫红, 陈骁, 吴炜, 高星宇   

  1. (浙江工业大学计算机科学与技术学院 杭州310023)
  • 收稿日期:2018-10-25 出版日期:2019-11-15 发布日期:2019-11-14
  • 通讯作者: 王卫红(1969-),男,硕士,教授,主要研究方向为图像图形处理、遥感与地理信息系统研究以及信息安全,E-mail:wwh@zjut.edu.cn
  • 作者简介:陈骁(1994-),男,硕士生,主要研究方向为遥感与地理信息;吴炜(1985-),男,博士,讲师,主要研究方向为遥感信息提取;高星宇(1993-),男,硕士生,主要研究方向为遥感信息提取。
  • 基金资助:
    本文受国家自然科学基金项目(61340058,41301473),浙江省自然科学基金重点项目(LZ14F020001)资助。

Method of Automatically Extracting Urban Water Bodies from High-resolution Images with Complex Background

WANG Wei-hong, CHEN Xiao, WU Wei, GAO Xing-yu   

  1. (College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China)
  • Received:2018-10-25 Online:2019-11-15 Published:2019-11-14

摘要: 城市水体分布信息对于理解城市水循环、热岛效应等地理现象具有重要意义。利用高分辨率影像进行水体提取和水体制图是常用的信息获取方式。由于城市环境背景复杂、高分影像光谱通道少以及水体在影像上分布比例不均匀等原因,将高分影像应用于水体自动提取仍存在较大难度。对此,基于国产高分影像发展一种面向复杂环境的城市水体自动化提取方法。首先,根据水体近红外通道灰度值较低的特征,自适应选取阈值进行分割,获取初始水体;其次,对初始水体进行缓冲以得到靶区域,使用高斯混合模型来表达其整体分布,通过改进期望最大算法估计水体类别分布参数后,使用最大似然法进行水体自动提取;在此基础上,针对粗提取水体中混杂阴影的问题,提出了融合特征方法来去除阴影,从而获得准确的水体提取结果。对上海市金山区的水体提取实验表明,使用所提方法可以有效提取实验影像中占比较小的水体结构,整体精度较目前常用的自动提取算法有明显提升。

关键词: 城市水体提取, 改进EM算法, 高斯混合模型, 类别不均衡, 阴影去除

Abstract: The distribution of urban water bodies is of great significance for people to understand the geographical phenomena such as the urban water circulation and the Heat-island Effect.It is common to obtain information by using high-resolution images for water extraction and water mapping.However,automatically extraction of water bodies by using the high-resolution images still is difficult for the complex background of the urban area,fewer spectral channels provided by the high-resolution images and the uneven distribution of water bodies in the images.This paper proposed an automatic extraction method of urban water bodies in complex background based on high-resolution images.First,adaptive threshold is selected for segmentation to gain the initial region of water,since water has a low gray value of the near infrared channel.Next,on the initial region,a buffering algorithm are used to obtain the target region of water extraction,and gauss mixture model and an expectation maximization algorithm is used to improve the distributionpara-meters of water.Then,the water bodies are extracted automatically using the maximum likelihood method with these parameters.As for the large number of shadow elements mixed in the rough extraction,a fusion features method is proposed to eliminate those noise points and obtain more accurate extraction result.The experiment results of water extraction in Jinshan show that the proposed method can effectively extract the structure of water bodies with small proportion in the experimental images,and perform well with high accuracy comparing to the commonly used automatic extraction algorithms.

Key words: Class imbalance, Extraction of urban water bodies, Gauss mixture model, Modified expectation maximization algorithm, Shadow removal

中图分类号: 

  • TP751
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