Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis

ZHANG Han; NI Weiping; YAN Weidong; BIAN Hui; WU Junzheng; LI Sha; JIN Xiao

doi:10.13203/j.whugis20140375

Volume 41 Issue 5

May 2016

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2016 > 41(5): 642-648. > DOI: 10.13203/j.whugis20140375

ZHANG Han, NI Weiping, YAN Weidong, BIAN Hui, WU Junzheng, LI Sha, JIN Xiao. Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis[J]. Geomatics and Information Science of Wuhan University, 2016, 41(5): 642-648. DOI: 10.13203/j.whugis20140375

Citation:

PDF (655 KB)

Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis

1.
Northwest Institute of Nuclear Technology, Xi'an 710024, China;
2.
School of Electronic Engineering, Xidian University, Xi'an 710071, China;
3.
Shenyang Artillery Academy, Shenyang 110161, China

More Information

Received Date: September 14, 2014
Published Date: May 04, 2016

Graphical Abstract

Abstract

Abstract

For pixel based SAR image change detection, the discrepancy images produced by the log ratio operation or Kullback-Leibler divergence cannot achieve satisfactory results in artificial target change detection. We introduce a fractal dimension into the construction of discrepancy images and define the Fractal Dimension-Log Ratio (FD-LR) image capable of detecting changes both from the natural targets and the artificial targets. A Gaussian mixture distribution is used to model the statistical properties of FD-LR. The Bayesian principle with expectation maximization-based parameter estimation is conducted to perform unsupervised thresholding on the FD-LR. To reduce speckle interferences , multiscale analysis and data fusion in the decision step are performed. Comparative experiments confirm the effectiveness of the proposed approach.
- SAR image,
- change detection,
- fractal dimension,
- multiscale analysis

FullText(HTML)

References (13)

References

[1]	Li Deren. Change Detection from Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2008, 28(s1):7-12(李德仁. 利用遥感影像进行变化检测[J]. 武汉大学学报·信息科学版, 2003, 28(s1):7-12)
[2]	Gong M G, Su L Z, Jia M,et al. Fuzzy Clustering with Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images[J]. IEEE Transactions on Fuzzy Systems,2013, 99:1-12
[3]	Inglada J, Mercier G. A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(5):1432-1445
[4]	Huang S Q, Cai X H, Chen S X,et al. Change Detection Method Based on Fractal Model and Wavelet Transform for Multi Temporal SAR Images[J]. International Journal of Applied Earth Observation and Geoinformation, 2011, 13(1):863-872
[5]	Salmasi M, Hashemi M M. Design and Analysis of Fractal Detector for High Resolution Radars[J]. Chaos, Solitons, and Fractals, 2009, 40(1):2133-2145
[6]	Celik T. A Bayesian Approach to Unsupervised Multiscale Change Detection in Synthetic Aperture Radar Images[J]. Signal Processing, 2010, 90:1471-1485
[7]	Xin F F, Jiao L C, Wang G T. SAR Image Change Detection Based on Memetic Algorithm[J]. J Infrared Millim Waves,2012,31(1):67-72(辛芳芳, 焦李成, 王桂婷. 基于Memetic算法的SAR图像变化检测[J]. 红外与毫米波学报, 2012, 31(1):67-72)
[8]	Bovolo F, Bruzzone L. A Detail-Preserving Scale-Driven Approach to Change Detection in Multitemporal SAR Images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(12):2963-2972
[9]	Gong Maoguo, Zhou Zhiqiang, Ma Jingjing. Change Detection in Synthetic Aperture Radar Images Based on Image Fusion and Fuzzy Clustering[J]. IEEE Transactions on Image Processing, 2012, 21(4):2141-2151
[10]	Chaudhuri B, Sarkar N. TextureSegmentation Using Fractal Dimension[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence Geoscience and Remote Sensing, 1995, 17(1):72-77
[11]	Ivanovici M, Richard N. Fractal Dimension of Color Fractal Images[J]. IEEE Transactions on Image Processing, 2011, 20(1):227-235
[12]	Pentland A P. Fractal-Based Description of Natural Scenes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence Geoscience and Remote Sensing, 1984, 6(6):661-674
[13]	Koenderink J J. The Structure of Images[J]. Biological Cybernetics, 1984, 50:363-370

[1]	GAO Xianjun, RAN Shuhao, ZHANG Guangbin, YANG Yuanwei. Building Extraction Based on Multi-feature Fusion and Object-Boundary Joint Constraint Network[J]. Geomatics and Information Science of Wuhan University, 2024, 49(3): 355-365. DOI: 10.13203/j.whugis20210520
[2]	ZENG Anmin, MING Feng, WU Fumei. Fusion Model for Long-Term Solutions to the Terrestrial Reference Frame Using Internal Constraints[J]. Geomatics and Information Science of Wuhan University, 2022, 47(9): 1447-1451. DOI: 10.13203/j.whugis20190453
[3]	LI Weilian, ZHU Jun, ZHANG Yunhao, FU Lin, HU Ya, YIN Lingzhi, DAI Yi. A Fusion Modeling and Interaction Method with Spatial Semantic Constraint for Debris Flow VR Scene[J]. Geomatics and Information Science of Wuhan University, 2020, 45(7): 1073-1081. DOI: 10.13203/j.whugis20180329
[4]	XIE Xuemei, SONG Yingchun, XIA Yuguo. An Active Set Algorithm of Conjugate Gradients for Adjustment Model with Interval Constraints[J]. Geomatics and Information Science of Wuhan University, 2019, 44(9): 1274-1281. DOI: 10.13203/j.whugis20170325
[5]	FAN Yaxin, ZHU Xinyan, GUO Wei, SHE Bing. Boundary-Constrained Max-p-Regions Problem and Its Heuristic Algorithm[J]. Geomatics and Information Science of Wuhan University, 2019, 44(6): 859-865. DOI: 10.13203/j.whugis20170253
[6]	XIE Xuemei, SONG Yingchun, XIAO Zhaobing. A Fast Search Algorithm in Adjustment Model with Inequality Constraint[J]. Geomatics and Information Science of Wuhan University, 2018, 43(9): 1349-1354. DOI: 10.13203/j.whugis20160435
[7]	YANG Yuanxi, ZENG Anmin, JING Yifan. GNSS Data Fusion with Functional and Stochastic ModelConstraints as well as Property Analysis[J]. Geomatics and Information Science of Wuhan University, 2014, 39(2): 127-131. DOI: 10.13203/j.whugis20130378
[8]	ZHU Qing, LI Haifeng, YANG Xiaoxia. Hierarchical Semantic Constraint Model for Focused Remote Sensing Information Services[J]. Geomatics and Information Science of Wuhan University, 2009, 34(12): 1454-1457.
[9]	ZENG Anmin, YANG Yuanxi, OUYANG Guichong. Sequential Adjustment with Constraints Among Parameters[J]. Geomatics and Information Science of Wuhan University, 2008, 33(2): 183-186.
[10]	ZHONG Min, YAN Haoming, ZHU Yaozhong, YU Yongqiang. Global Ocean Angular Momentum Variability and Geodetic Constraint[J]. Geomatics and Information Science of Wuhan University, 2003, 28(6): 697-702.

Cited By

Cited by

Periodical cited type(1)

任亚飞，郑玉丽，姚雷博. 基于图像识别的淬火过程中钢球计数研究. 拖拉机与农用运输车. 2021(06): 52-54+58 .

Other cited types(3)

Get Citation

PDF

XML

Article views PDF downloads Cited by(4)

Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis

Abstract

References

Related Articles

Cited by

Periodical cited type(1)

Other cited types(3)

Catalog

Related

Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis

Abstract

References

Related Articles

Cited by

Periodical cited type(1)

Other cited types(3)

Catalog

Related

Export File

Citation

Format

Content