Browse > Article
http://dx.doi.org/10.3837/tiis.2018.04.017

Change Detection in Bitemporal Remote Sensing Images by using Feature Fusion and Fuzzy C-Means  

Wang, Xin (College of Computer and Information, Hohai University)
Huang, Jing (Business School of Hohai University)
Chu, Yanli (College of Computer and Information, Hohai University)
Shi, Aiye (College of Computer and Information, Hohai University)
Xu, Lizhong (College of Computer and Information, Hohai University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.4, 2018 , pp. 1714-1729 More about this Journal
Abstract
Change detection of remote sensing images is a profound challenge in the field of remote sensing image analysis. This paper proposes a novel change detection method for bitemporal remote sensing images based on feature fusion and fuzzy c-means (FCM). Different from the state-of-the-art methods that mainly utilize a single image feature for difference image construction, the proposed method investigates the fusion of multiple image features for the task. The subsequent problem is regarded as the difference image classification problem, where a modified fuzzy c-means approach is proposed to analyze the difference image. The proposed method has been validated on real bitemporal remote sensing data sets. Experimental results confirmed the effectiveness of the proposed method.
Keywords
Remote sensing image; change detection; feature fusion; fuzzy c-means;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Mustafa Hayri Kesikoglu, U. H Ataseve and C. Ozkan, "Unsupervised change detection in satellite images using fuzzy c-means clustering and principal component analysis," ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XL-7/W2, no. 7, pp. 129-132, November 2013.
2 Lorenzo Bruzzone and Diego Fernàndez Prieto, "Automatic analysis of the difference image for unsupervised change detection," IEEE Transactions on Geoscience and Remote sensing, vol. 38, no. 3, pp. 1171-1182, May, 2000.   DOI
3 Lu Jia, Ming Li, Peng Zhang and YanWu, "SAR Image Change Detection Based on Correlation Kernel and Multistage Extreme Learning Machine," IEEE Transactions on Geoscience and Remote sensing, vol. 54, no. 10, pp. 5993-6006, October, 2016.   DOI
4 Maoguo Gong, Puzhao Zhang, Linzhi Su and Jia Liu, "Coupled Dictionary Learning for Change Detection From Multisource Data," IEEE Transactions on Geoscience and Remote sensing, vol. 54, no. 12, pp. 7077-7091, December, 2016.   DOI
5 Maoguo Gong, Tao Zhan, Puzhao Zhang and Qiguang Miao, "Superpixel-Based Difference Representation Learning for Change Detection in Multispectral Remote Sensing Images," IEEE Transactions on Geoscience and Remote sensing, vol. 55, no. 5, pp. 2658-2673, May, 2017.   DOI
6 Xiaofeng Wu, Fen Yang and Roly Lishman, "Land cover change detection using texture analysis," Journal of Computer Science, vol.6, no.1, pp. 92-100, January, 2010.   DOI
7 Jiang Li and Ram M. Narayanan, "A shape-based approach to change detection of lakes using time series remote sensing images," IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 11, pp. 2466-2477, November, 2003.   DOI
8 Neil C. Rowe and Lynne L. Grewe, "Change detection for linear features in aerial photographs using edge-finding," IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 7, pp. 1608-1612, July, 2001.   DOI
9 Victor-Emil Neagoe, Radu-Mihai Stoica, Alexandru-Ioan Ciurea,Lorenzo Bruzzone and Francesca Bovolo, "Concurrent Self-Organizing Maps for Supervised/Unsupervised Change Detection in Remote Sensing Images" IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 8, pp. 3525-3533, August, 2014.   DOI
10 Michele Volpi, Devis Tuia, Francesca Bovolo, Mikhail Kanevski and Lorenzo Bruzzonec, "Supervised change detection in VHR images using contextual information and support vector machines," International Journal of Applied Earth Observation and Geoinformation, vol. 20, pp. 77-85, Febuary, 2013.   DOI
11 Natalia Sofina and Manfred Ehlers, "Building change detection using high resolution remotely sensed data and GIS," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 8, pp. 3430-3438, August, 2016.   DOI
12 Kun Ding, Chunlei Huo, Yuan Xu, Zisha Zhong and Chunhong Pan, "Sparse Hierarchical Clustering for VHR Image Change Detection," IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 3, pp. 577-581, March, 2015.   DOI
13 Nikhil R. Pal and James C. Bezdek, "On cluster validity for the fuzzy c-means model," IEEE Transactions on Fuzzy systems, vol. 3, no. 3, August, 1995.
14 Susmita Ghosh, Niladri Shekhar Mishra and Ashish Ghosh, "Unsupervised change detection of remotely sensed images using fuzzy clustering," in Proc. of IEEE International Conference on Advances in Pattern Recognition, pp. 385-388, February 4-6, 2009.
15 Krishna Kant Singh, AkanshaMehrotra, M.J.Nigam and Kirat Pal, "Unsupervised change detection from remote sensing images using hybrid genetic FCM," in Proc. of IEEE International Conference on Engineering and Systems, pp. 1-5, April, 2013.
16 Robert Martin Haralick, K. Shanmugam and Its'Hak Dinstein, "Textural features for image classification," IEEE Transactions on systems, man, and cybernetics, vol. 3, no. 6, pp. 610-621, December, 1973.   DOI
17 Juan P. Ardila, Wietske Bijker, Valentyn A. Tolpekin and Alfred Stein, "Quantification of crown changes and change uncertainty of trees in an urban environment," ISPRS journal of photogrammetry and remote sensing, vol. 2012, no. 74, pp. 41-55, November, 2012.
18 Xin. Wang, Guofang Lv and Lizhong Xu, "Infrared dim target detection based on visual attention," Infrared Physics & Technology, vol. 55, no. 6, pp. 513-521, June, 2012.   DOI
19 Xin Wang, Siqiu Shen, Chen Ning, Fengchen Huang and Hongmin Gao, "Multi-class remote sensing object recognition based on discriminative sparse representation," Applied Optics, vol. 55, no. 6, pp. 1381-1394, June, 2016.   DOI
20 Mengxi Xu, Quansen Sun, Yingshu Lu, Fengchen Huang and Chenrong Huang, "A Novel Fast Remote Sensing Targets Detection Model based on KSC-SBOW," International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 9, no. 3, pp. 341-354, March 2016.
21 Mengxi Xu, Quansen Sun, Zhenyu He and Jianqiang Shi, "Band selection for hyperspectral images based on particle swarm optimization and differential evolution algorithms with hybrid encoding," Journal of Computational Methods in Sciences and Engineering, vol. 16, no. 3, pp. 629-640, October, 2016.   DOI
22 Adel Shalaby, Ryutaro Tateishi, "Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt," Applied Geography, vol. 27, no. 1, pp. 28-41, January, 2007.   DOI
23 Ming Hao, Wenzhong Shi, Hua Zhang and Chang Li, "Unsupervised Change Detection With Expectation-Maximization-Based Level Set," IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 1, January, 2014.
24 Shaun Quegan, Thuy Le Toan, Jiong Jiong Yu, Florence Ribbes and Nicolas Floury, "Multitemporal ERS SAR analysis applied to forest mapping," IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 2, pp. 741-753, March 2000.   DOI
25 Sicong Liu, Lorenzo Bruzzone, Francesca Bovolo and Peijun Du, "Unsupervised Multitemporal Spectral Unmixing for Detecting Multiple Changes in Hyperspectral Images," IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 5, pp. 2733-2748, May 2016.   DOI
26 Zhen Lei, Tao Fang, Hong Huo and Deren Li, "Bi-Temporal Texton Forest for Land Cover Transition Detection on Remotely Sensed Imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 5, pp. 1227-1237, February 2014.   DOI
27 T. A. Pawar, "Change Detection Approach for Images Using Image Fusion and C-means Clustering Algorithm," International Journal of Advanced Research in Computer Science and Management Studies, vol. 2, no. 10, pp. 303-307, October, 2014.