结合阴影补偿的对象级高分辨率遥感影像多尺度变化检测
Object-based change detection method for high-resolution remote sensing image combining shadow compensation and multi-scale fusion
- 通信学报 2018年39卷第9期 页码：159-167
- 作者机构：
1. 南京信息工程大学电子与信息工程学院，江苏 南京 210044
2. 南京信息工程大学地理与遥感学院，江苏 南京 210044
3. 河海大学计算机与信息学院，江苏 南京 211100
4. 徐州工程学院江苏省智慧工业控制技术重点建设实验室，江苏 徐州 221000
- 作者简介：
[ "王超（1984-），男，山东济南人，博士，南京信息工程大学讲师，主要研究方向为高分辨率遥感影像处理。" ]
[ "张雪红（1980-），男，江西上饶人，博士，南京信息工程大学教授，主要研究方向为农业气象灾害遥感及环境资源遥感。" ]
[ "石爱业（1969-），男，江苏泗洪人，博士，河海大学副教授，主要研究方向为高分辨率遥感影像处理。" ]
[ "厉丹（1981-），女，江苏徐州人，博士，徐州工程学院副教授，主要研究方向为模式识别与计算机视觉。" ]
[ "申祎（1996-），男，河南新乡人，南京信息工程大学硕士生，主要研究方向为高分辨率遥感影像处理。" ]
- 基金信息：国家自然科学基金资助项目(61601229);江苏省自然科学基金资助项目(BK20160966);中国博士后科学基金资助项目(2017M611866);江苏省高等学校优势学科(1081080015001);江苏省智慧工业控制技术重点建设实验室开放课题基金资助项目(JSKLIIC201705)
DOI：10.11959/j.issn.1000-436x.2018168
中图分类号： TP391-
网络首发：2018-09，
纸质出版：2018-09-25
- 稿件说明：
移动端阅览
王超, 张雪红, 石爱业, 等. 结合阴影补偿的对象级高分辨率遥感影像多尺度变化检测[J]. 通信学报, 2018,39(9):159-167.
Chao WANG, Xuehong ZHANG, Aiye SHI, et al. Object-based change detection method for high-resolution remote sensing image combining shadow compensation and multi-scale fusion[J]. Journal on Communications, 2018, 39(9): 159-167.
王超, 张雪红, 石爱业, 等. 结合阴影补偿的对象级高分辨率遥感影像多尺度变化检测[J]. 通信学报, 2018,39(9):159-167. DOI： 10.11959/j.issn.1000-436x.2018168.
Chao WANG, Xuehong ZHANG, Aiye SHI, et al. Object-based change detection method for high-resolution remote sensing image combining shadow compensation and multi-scale fusion[J]. Journal on Communications, 2018, 39(9): 159-167. DOI： 10.11959/j.issn.1000-436x.2018168.
摘要
阴影是遥感影像的解译标志之一，然而在高分辨率遥感影像变化检测中，阴影所产生的“伪变化”是导致错检的主要原因之一。为此，提出了一种结合阴影补偿与多尺度融合的对象级高分遥感影像变化检测方法。在面向对象的变化检测框架下，首先提取遥感影像中的地物阴影，然后对多尺度变化检测进行阴影补偿。其中，通过构建一种尺度间互信息最小化的目标函数实现了尺度参数的自适应提取。在此基础上，结合所提出的阴影补偿因子，设计了一种基于D-S证据理论的决策级多尺度融合策略，并进一步对变化强度等级进行了划分。实验证明，该方法能够较好地解决阴影所导致的错检问题，显著提高变化检测精度。
Abstract
As an interpreting symbol of remote sensing images
shadow
however
brings about “pseudo changes”
which is one of the main sources leading to error detection in high-resolution remote sensing image change detection.For this issue
an object-based high-resolution remote sensing image change detection method was proposed combining with shadow compensation and multi-scale fusion.In the object orientation detection framework
the shadows in the remote sensing images were extracted.Then multi-scale change detection was conducted with shadow compensation.In the process
an objective function was constructed of mutual scale information minimization to realize the adaptive extraction of scale parameters.Based on this
combined with the shadow compensation factor
a multi-scale decision-level fusion strategy built on D-S theory of evidence was designed
and the levels of change intensity were further divided.The experiments show that the method is effective in solving the error detection problem caused by shadow
significantly improving the precision of change detection.
关键词
Keywords
references
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