帮助 关于我们

返回检索结果

高分辨率遥感影像特征分割及算法评价分析
Research on High Resolution Remote Sensing Image Segmentation. Methods Based on Features and Evaluation of Algorithms

查看参考文献15篇

明冬萍 1   骆剑承 1   周成虎 1   王晶 2  
文摘 图像分割一直是图像处理和计算机视觉领域中的一项关键技术。本文首先从遥感影像地学处理与应用的角度阐述了影像分割技术对于遥感信息提取和目标识别的重要性.然后提出了基于特征的高分辨率遥感影像信息提取技术框架.建立了一套基于特征的遥感影像分割方法及分类体系。同时,鉴于遥感影像分割方法评价的重要性,阐述了一种高分辨率遥感影像分割方法评价的思路.并对几种典型的基于特征的遥感影像分割方法进行定性和定量的试验和评价.对其各自的性能和适用面进行对比分析。最后.指出了遥感影像特征分割方法所存在的问题及其发展趋势。
其他语种文摘 Image segmentation is a key technique "in image processing and computer vision field. From the point of view of geo-processing and application of remote sensing images, this paper emphasizes the importance of image segmentation for information extraction and targets recognition from remote sensing images and sets a classification system of common remote sensing image segmentation methods. In addition, this paper states the thoughts of high resolution RS image segmentation methods evaluation and tests it by evaluating four typical image segmentation algorithms based on features with six images qualitatively and quantitatively. The four typical image segmentation algorithms are Max-Entropy (ME), Split&Merge (SM), improved Gauss Markov Random Field(GMRF) and Orientation&Phase(OP). In the qualitative evaluation, this paper analyses these algorithms in terms of their rationale and gets a rough evaluation. In the quantitative evaluation, image complexity is taken into account firstly and five measures are employed. The five measures are removed region rumber, nonuniformity within region measure, contrast across region measure, variance contrast across region measure and edge gradient measure. The qualitatively and quantitatively evaluation results are important to perform the optimal selection of segmentation algorithm in practical work. In the end, this paper draws some conclusions about high resolution remote sensing image segmentation and enumerates the flaws of image segmentation methods evaluation, especially it concludes the application prospect of high resolution RS image segmentation.
来源 地球信息科学 ,2006,8(1):103-109 【扩展库】
关键词 高分辨率遥感 ; 影像分割 ; 特征 ; 信息提取 ; 算法评价
地址

1. 中国科学院地理科学与资源研究所, 北京, 100101  

2. 西北工业大学计算机学院, 西安, 710072

语种 中文
文献类型 研究性论文
ISSN 1560-8999
学科 自动化技术、计算机技术
基金 国家自然科学基金项目 ;  中国科学院地理科学与资源研究所知识创新工程领域前沿项目
文献收藏号 CSCD:2307867

参考文献 共 15 共1页

1.  Zhang Yujin. Image Segmentation. Image Segmentation,2001 被引 4    
2.  Nikhil R Pal. A review on image segmentation techniques. Pattern Recognition,1993,26(9):1277-1294 被引 234    
3.  Y J Zhang. A survey on evaluation methods for image segmentation. Pattern Recognition,1996,29(8):1335-1346 被引 74    
4.  Luo Xiping. A survey on image segmentation methods. Pattern Recognition & Artificial Intelligence,1999,12(3):300-312 被引 3    
5.  Valmir C Barbosa. A neural system for deforestation monitoring on Landsat images of the Amazon Region. International Journal of Approximate Reasoning,1994,11(4):321-359 被引 1    
6.  Chen Qiuxiao. Multiple features based analysis of remotely sensed imagery. Remote Sensing for Land & Resources,2003,1:5-7 被引 1    
7.  Peng-yeng Yin. Maximum entropy-based optimal threshold selection using deterministic reinforcement learning with controlled randomization. Signal Processing,2002,82(7):993-1006 被引 1    
8.  Diogo Cortez. Manuel Menezes de Sequeira. Signal Processing:Image Communication,1995,6(6):485-498 被引 3    
9.  Zhao Feng. A new method for image segmentation. Journal of Northwestern Polytechnical University,2000,18(1):116-120 被引 1    
10.  R Molina. Compound Gauss-Markov random fields for astronomical image restoration. Vistas in Astronomy,1996,40(4):539-546 被引 1    
11.  Zhang Cui. SAR image segmentation based on Markov random field model. Remote Sensing Technology and Application,2001,16(1):66-68 被引 2    
12.  Din-chang Tseng. A genetic algorithm for MRF-based segmentation of multi-spectral textured images. Pattern Recognition Letters,1999,20(14):1499-1510 被引 3    
13.  Lauren O'Donnell. Phase-Based Semiautomatic Image Segmentation. http://www.ai.mit.edu/research/abstracts/abstracts2001/medical-vision/04odonnell.pdf 被引 1    
14.  carol. Image Segmentation by Directed Region Subdivision. wins.uva.nl/~gevers/pub/paper_jarusalem.ps 被引 1    
15.  Wang Xiaodong. Algorithm Design and Analysis. Algorithm Design and Analysis,2003 被引 1    
引证文献 13

1 张友静 城市植被尺度鉴别与分类研究 地理与地理信息科学,2007,23(6):54-57
被引 7

2 江淼 航空与卫星影像数据多尺度分割对比研究 地球信息科学,2007,9(5):115-120,封3
被引 1

显示所有13篇文献

论文科学数据集
PlumX Metrics
相关文献

 作者相关
 关键词相关
 参考文献相关

版权所有 ©2008 中国科学院文献情报中心 制作维护:中国科学院文献情报中心
地址:北京中关村北四环西路33号 邮政编码:100190 联系电话:(010)82627496 E-mail:cscd@mail.las.ac.cn 京ICP备05002861号-4 | 京公网安备11010802043238号