量子多尺度融合的高分卫星影像建筑物变化检测

doi:10.13474/j.cnki.11-2246.2024.0612

测绘通报 ›› 2024, Vol. 0 ›› Issue (6): 65-70,126.doi: 10.13474/j.cnki.11-2246.2024.0612

• 学术研究 • 上一篇

量子多尺度融合的高分卫星影像建筑物变化检测

张燕平¹, 张卡^2,3,4,5, 赵立科^6,7, 陶厦^2,3, 张帮⁸, 王玉军^6,7, 顾桢^2,3, 刘浩林^2,3

1. 江苏省测绘产品质量监督检验站, 江苏南京 210013;
2. 虚拟地理环境教育部重点实验室 (南京师范大学), 江苏南京 210023;
3. 南京师范大学地理科学学院, 江苏南京 210023;
4. 江苏省地理信息资源开发与利用协同创新中心, 江苏南京 210023;
5. 镇江市精勤测绘有限公司, 江苏镇江 212009;
6. 江苏省地质调查研究院, 江苏南京 210018;
7. 自然资源江苏省卫星应用技术中心, 江苏南京 210018;
8. 苏州市消防救援支队, 江苏苏州 215000

收稿日期:2023-12-01 发布日期:2024-06-27
通讯作者: 张卡。E-mail:zhangka81@126.com
作者简介:张燕平(1981—),男,硕士,高级工程师,主要从事地理信息处理方面的研究工作。E-mail:zhypcumt@163.com
基金资助:
国家自然科学基金(42271342;42071301);江苏高校优势学科建设工程资助项目(164320H116)

Change detection of buildings in high-resolution satellite images based on quantum multi-scale fusion

ZHANG Yanping¹, ZHANG Ka^2,3,4,5, ZHAO Like^6,7, TAO Xia^2,3, ZHANG Bang⁸, WANG Yujun^6,7, GU Zhen^2,3, LIU Haolin^2,3

1. Jiangsu Quality Supervision and Inspection Station for Surveying and Mapping Products, Nanjing 210013, China;
2. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China;
3. School of Geographiy, Nanjing Normal University, Nanjing 210023, China;
4. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China;
5. Zhenjiang Jingqin Surveying and Mapping Co., Ltd., Zhenjiang 212009, China;
6. Geological Survey of Jiangsu Province, Nanjing 210018, China;
7. Natural Resources Satellite Application Technology Center of Jiangsu Province, Nanjing 210018, China;
8. Suzhou Fire Rescue Detachment, Suzhou 215000, China

Received:2023-12-01 Published:2024-06-27

摘要/Abstract

摘要： 为了提高传统基于像元的高分辨率卫星影像变化检测方法的精度,本文提出了一种基于量子多尺度融合的高分卫星影像建筑物变化检测算法。首先,对双时相高分辨率卫星影像进行多尺度分割,构成多尺度影像数据集;然后,对多尺度影像数据集进行迭代慢特征变换,得到不同尺度的变化强度图,再利用量子理论对多尺度变化强度图进行融合,以得到融合后的变化强度图;最后,通过最大类间方差法完成变化强度图的阈值分割,得到二值化变化检测结果。利用两组不同时相的实际高分卫星影像,对本文算法进行了试验验证。试验结果表明,与单一尺度面向对象变化检测方法和熵权法多尺度融合方法相比,本文算法可以取得更高的建筑物变化检测精度。

关键词: 高分卫星影像, 建筑物变化检测, 量子理论, 迭代慢特征分析, 多尺度融合

Abstract: In order to improve the accuracy of the traditional high-resolution satellite image change detection method based on pixels, this paper proposes a building change detection algorithm based on quantum multi-scale fusion for high-resolution satellite images. Firstly, multi-scale segmentation of dual temporal high-resolution satellite images is carried out to form a multi-scale image dataset.Secondly, the multi-scale image dataset is transformed by iterative slow feature transformation to obtain the change intensity map of different scales, and then the multi-scale change intensity map is fused by quantum theory to obtain the fused change intensity map.Finally, the threshold segmentation of the change intensity map is completed by the maximum variance between classes method, and the binary change detection results are obtained. Two groups of real high-resolution satellite images with different time phases are used to verify the algorithm in this paper. The experimental results show that compared with the single-scale object-oriented change detection method and the multi-scale fusion method of entropy weight method, the algorithm in this paper can achieve higher accuracy in building change detection.

Key words: high-resolution satellite image, building change detection, quantum theory, iterative slow feature analysis, multi-scale fusion

中图分类号:

P237

张燕平, 张卡, 赵立科, 陶厦, 张帮, 王玉军, 顾桢, 刘浩林. 量子多尺度融合的高分卫星影像建筑物变化检测[J]. 测绘通报, 2024, 0(6): 65-70,126.

ZHANG Yanping, ZHANG Ka, ZHAO Like, TAO Xia, ZHANG Bang, WANG Yujun, GU Zhen, LIU Haolin. Change detection of buildings in high-resolution satellite images based on quantum multi-scale fusion[J]. Bulletin of Surveying and Mapping, 2024, 0(6): 65-70,126.

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量子多尺度融合的高分卫星影像建筑物变化检测

Change detection of buildings in high-resolution satellite images based on quantum multi-scale fusion

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