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遥感技术与应用  2016, Vol. 31 Issue (1): 186-193    DOI: 10.11873/j.issn.1004-0323.2016.1.0186
数据与图像处理     
顾及面积和位置差异的高分遥感影像分割质量评价方法
毛召武,程结海,袁占良
(河南理工大学测绘与国土信息工程学院,河南 焦作454003)
A Method to Assessing the Segmentation Quality of High-spatial Resolution Remote Sensing Images by Considering Area and Position Discrepancies
Mao Zhaowu,Cheng Jiehai,Yuan Zhanliang
(School of Surveying & Land Information Engineering,
Henan Polytechnic University,Jiaozuo 454003,China)
 全文: PDF(4924 KB)  
摘要:

高分遥感影像分割质量对面向对象分类精度有着重要的影响,良好的影像分割质量有利于得到较高的分类精度。对高分遥感影像分割质量进行评价,从而找到最优的分割结果就显得十分重要。通过对比参考对象和分割对象之间的面积和位置差异,提出了一种新的高分遥感影像分割质量评价方法。将该评价方法应用于GeoEye\|1高分遥感影像分割质量评价,试验结果表明:该评价方法能客观地评价影像分割质量,所得到的最优分割结果与参考对象边界匹配程度高,有利于影像后续的分类。

关键词: 高分遥感影像分割质量评价面积差异位置差异    
Abstract:

The segmentation quality of high\|spatial resolution remote\|sensing images has a significantly impact on image classification accuracy.The better image segmentation results will facilitate to get higher classification accuracy.Therefore,it’s necessary to obtain optimal segmentation results by assessing image segmentation quality.A method for assessing the segmentation of high\|spatial resolution remote\|sensing images is proposed by measuring both area and position discrepancies between reference image and segmented image in this paper.This method has been applied to assess the segmentation result quality of image from GeoEye\|1 satellite.The experimental results show that this new method can objectively assess the image segmentation quality,and with the high matching degree of boundary between the obtained optimal segmentation results and reference image is benefit for subsequent image classification.

Key words: High-spatial resolution remote sensing images    Segmentation quality assessment    Area discrepancy    Position discrepancy
收稿日期: 2014-12-05 出版日期: 2016-04-05
:  TP 751.1  
基金资助:

国家自然科学基金项目(41271347),河南省教育厅科学技术重点研究项目(14A420004),河南省高校基本科研业务费专项资金资助(NSFRF140114),河南理工大学博士基金项目(B2014\|014)。

通讯作者: 程结海(1980-),男,安徽太湖人,副教授,博士,主要从事空间信息分析与不确定性研究。Email:chengjiehai@gmail.com。    
作者简介: 毛召武(1990-),男,安徽肥西人,硕士研究生,主要从事高分遥感信息提取方面的研究。Email:mzhw1990@163.com。
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引用本文:

毛召武,程结海,袁占良. 顾及面积和位置差异的高分遥感影像分割质量评价方法[J]. 遥感技术与应用, 2016, 31(1): 186-193.

Mao Zhaowu,Cheng Jiehai,Yuan Zhanliang. A Method to Assessing the Segmentation Quality of High-spatial Resolution Remote Sensing Images by Considering Area and Position Discrepancies. Remote Sensing Technology and Application, 2016, 31(1): 186-193.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2016.1.0186        http://www.rsta.ac.cn/CN/Y2016/V31/I1/186

[1]Gong Peng,Li Xia,Xu Bing.Interpretation Theory and Application Method Development for Information Extraction from High Resolution Remotely Sensed Data[J].Journal of Remote Sensing,2006,10(1):1-5.[宫鹏,黎夏,徐冰.高分辨率影像解译理论与应用方法中的一些研究问题[J].遥感学报,2006,10(1):1-5.]

[2]Liu Jianhua,Mao Zhengyuan.A Survey on Segmentation Techniques and Application Strateggy of High Spatial Resolution Remote Sensing Imagery[J].Remote Sensing Informstion,2009,(6):95-101.[刘建华,毛政元.高空间分辨率遥感影像分割方法研究综述[J].遥感信息,2009,(6):95-101.]

[3]Zhang Bo.The Multiscale Classification Method of High Resolution Remote Sensing[D].Chengdu:University of Electronic Science and Technology of China,2013.[张博.高分辨率遥感影像多尺度分类方法研究[D].成都:电子科技大学,2013.]

[4]Lu D,Weng Q.A Survey of Image Classification Methods and Techniques for Improving Classification Performance[J].International Journal of Remote Sensing,2007,28(5):823-870.

[5]Blaschke T,Lang S,Lorup E,et al.Object-oriented Image Processing in an Integrated GIS/Remote Sensing Environment and Perspectives for Environmental Applications[J].Environmental Information for Planning,Politics and the Public,2000,2:555-570.

[6]Benz U C,Hofmann P,Willhauck G,et al.Multi-resolution,Object-oriented Fuzzy Analysis of Remote Sensing Data for GIS-ready Information[J].ISPRS Journal of Photogrammetry and Remote Sensing,2004,58(3):239-258.

[7]Fu Zhuo,Hu Jiping,Tan Qulin,et al.The Methods of Image Segmentation on Application and Analysis of Remote Sensing Image[J].Remote Sensing Technology and Application,2006,21(5):456-462.[付卓,胡吉平,谭衢霖,等.遥感应用分析中影像分割方法[J].遥感应用与技术,2006,21(5):456-462.]

[8]Huang Huiping.Scale Issues in Object-oriented Image Analysis[D].Beijing:Institute of Remote Sensing Applications,Chinese Academy of Sciences,2003.[黄惠萍.面向对象影像分析中的尺度问题研究[D].北京:中国科学院遥感应用研究所,2003.]

[9]Carleer A P,Debeir O,Wolff E.Assessment of Very High Spatial Resolution Satellite Image Segmentations[J].Photogrammetric Engineering & Remote Sensing,2005,71(11):1285-1294.

[10]Lang S,Schpfer E,Langanke T.Combined Object-based Classification and Manual Interpretation-synergies for A Quantitative Assessment of Parcels and Biotopes[J].Geocarto International,2009,24(2):99-114.

[11]Clinton N,Holt A,Scarborough J,et al.Accuracy Assessment Measures for Object-based Image Segmentation Goodness[J].Photogrammetric Engineering and Remote Sensing,2010,76(3):289-299.

[12]Weidner U.Contribution to the Assessment of Segmentation Quality for Remote Sensing Applications[J].International Archives of Photogrammetry,Remote Sensing and Spatial Information Science,2008,37(B7):479-484.

[13]Neubert M,Meinel G.Evaluation of Segmentation Programs for High Resolution Remote Sensing Applications[C]//Germany Proceedings the Joint ISPRS/EARSeL Workshop High Resolution Mapping from Space 2003.Hannover,2003.

[14]Bie Qiang,He Lei,Zhao Chuanyan.Study on Vegetation Information Extraction based on Object-oriented Image Analysis[J].Remote Sensing Technology and Application,2014,29(1):164-171.[别强,何磊,赵传燕.基于影像融合和面向对象技术的植被信息提取研究[J].遥感技术与应用,2014,29(1):164-171.]

[15]Zhang Y J.A Survey on Evaluation Methods for Image Segmentation[J].Pattern Recognition Letters,1996,29(8):1335-1346.

[16]Zhang H,Fritts J E,Goldman S A.Image Segmentation Evaluation:A Survey of Unsupervised Methods[J].Computer Vision and Image Understanding,2008,110(2):260-280.

[17]Cheng J H,Bo Y C,Zhu Y X,et al.A Novel Method for Assessing the Segmentation Quality of High-spatial Resolution Remote-sensing Images[J].International Journal of Remote Sensing,2014,35(10):3861-3839.

[18]Mller M,Lymburner L,Volk M.The Comparison Index:A Tool for Assessing the Accuracy of Image Segmentation[J].International Journal of Applied Earth Observation and Geoinformation,2007,9(3):311-321.

[19]Lucieer A,Stein A.Existential Uncertainty of Spatial Objects Segmented from Satellite Sensor Imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2002,40(11):2518-2521.

[20]Zhan Q,Molenaar M,Tempfli K,et al.Quality Assessment for Geo-spatial Objects Derived from Remotely Sensed Data[J].International Journal of Remote Sensing,2005,26(14):2953-2974.

[21]Chen Qiuxiao,Chen Shupeng,Zhou Chenghu.Segmentation Approach for Remote Sensing Image based on Local Homogeneity Gradient and Its Evaluation[J].Journal of Remote Sensing,2006,10(3):357-365.[陈秋晓,陈述彭,周成虎.基于局域同质性梯度的遥感图像分割方法及其评价[J].遥感学报,2006,10(3):357-365.]

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