基于特征位置优选整合的快速城区检测算法

doi:10.3969/j.issn.0372-2112.2015.07.018

电子学报 ›› 2015, Vol. 43 ›› Issue (7): 1369-1374.DOI: 10.3969/j.issn.0372-2112.2015.07.018

基于特征位置优选整合的快速城区检测算法

师皓¹, 陈禾¹, 毕福昆², 庞枫骞¹, 杨小婷¹

1. 北京理工大学信息与电子学院, 北京 100081;
2. 北方工业大学信息工程学院, 北京 100144

收稿日期:2013-11-04 修回日期:2014-01-21 出版日期:2015-07-25
- 通讯作者:
- 毕福昆
- 作者简介:
- 师皓 男,1986年4月出生,河北石家庄人.2012年在北京化工大学获得控制科学与工程硕士学位,现为北京理工大学博士研究生.研究方向为:遥感图像处理、嵌入式系统研发. E-mail:shihao@bit.edu.cn;陈禾 女,1970年3月出生,辽宁沈阳人.1998年在哈尔滨工业大学获得工学博士学位,2000年北京理工大学通信与信息工程博士后流动站出站.现为北京理工大学信息与电子学院教授,博士生导师.研究方向为:遥感图像及雷达信号处理、超大规模集成电路设计. E-mail:chenhe@bit.edu.cn
- 基金资助:
- 国家863高技术研究发展计划 (No.2011AA120201)

A Real-Time Urban Area Detection Algorithm Based on Feature Location Optimization and Integration

SHI Hao¹, CHEN He¹, BI Fu-kun², PANG Feng-qian¹, YANG Xiao-ting¹

1. School of Information and Electronic, Beijing Institute of Technology, Beijing 100081, China;
2. Department of Information Engineering, North China University of Technology, Beijing 100144, China

Received:2013-11-04 Revised:2014-01-21 Online:2015-07-25 Published:2015-07-25

摘要/Abstract

摘要：

遥感图像中城市区域的自动分析解译是遥感对地观测领域重要的应用方向,针对自动高效城区检测的迫切需求,提出了一种基于遥感图像的城区区域快速检测算法.首先通过智能去雾处理降低薄雾气象条件对检测的干扰,然后通过快速的关键点搜寻进行城区特征位置初选,并以全局与局部约束相结合的策略筛选出高置信度的城区特征位置,最后通过高斯渲染加权的方法整合城区特征位置,并在获得的城区高斯加权图上自适应分割出最终的城区.本算法使用Google提供的卫星图像进行算法验证测试,可得到准确的检测结果.本检测算法可满足遥感图像城区检测自动化、实时化的需求,大大减小了人工判图的工作量,能够广泛应用于机载或星载平台.

关键词: 城区检测, 遥感图像处理, 去雾处理, 特征点提取, 实时处理

Abstract:

According to the needs of automatic and efficient detection for the urban areas,an urban area detection algorithm is proposed in this paper.First,the intelligent haze removal processing is used to reduce the interference in detection.Second,the primary feature locations of urban are extracted by the feature points.Then with the combination of the global and local constraints,the highly reliable urban locations are selected.Finally,the urban characteristic locations are integrated by the method of Gaussian rendering weighted and the final urban areas are obtained through adaptive segmentation.The algorithm is tested using Google satellite images to get accurate results.It can meet the needs for automatic and real-time detection in the remote sensing image of urban areas and greatly reduce the workload of manual interpretation.

Key words: urban area detection, remote sensing image processing, image haze removal, feature points extraction, real-time processing

中图分类号:

TP751

师皓, 陈禾, 毕福昆, 庞枫骞, 杨小婷. 基于特征位置优选整合的快速城区检测算法[J]. 电子学报, 2015, 43(7): 1369-1374.

SHI Hao, CHEN He, BI Fu-kun, PANG Feng-qian, YANG Xiao-ting. A Real-Time Urban Area Detection Algorithm Based on Feature Location Optimization and Integration[J]. Acta Electronica Sinica, 2015, 43(7): 1369-1374.

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基于特征位置优选整合的快速城区检测算法

A Real-Time Urban Area Detection Algorithm Based on Feature Location Optimization and Integration

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