Object-based change detection method for high-resolution remote sensing image combining shadow compensation and multi-scale fusion

Chao WANG; Xuehong ZHANG; Aiye SHI; Dan LI; Yi SHEN

doi:10.11959/j.issn.1000-436x.2018168

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Object-based change detection method for high-resolution remote sensing image combining shadow compensation and multi-scale fusion

Papers | 更新时间：2024-06-05

- Object-based change detection method for high-resolution remote sensing image combining shadow compensation and multi-scale fusion
- Journal on Communications Vol. 39, Issue 9, Pages: 159-167(2018)
- 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：
- 基金信息：
  
  National Natural Science Foundation of China(61601229);The Natural Science Foundation of Jiangsu Province(BK20160966);China Postdoctoral Science Foundation Funded Project(2017M611866);Priority Academic Program Development of Jiangsu Higher Education Institutions(1081080015001);Key Laboratory of Intelligent Industrial Control Technology of Jiangsu Province Open Foundation(JSKLIIC201705)
- DOI：10.11959/j.issn.1000-436x.2018168
  CLC： TP391
- Online First：2018-09，
  
  Published：25 September 2018
- 稿件说明：
移动端阅览
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：

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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