Remote Sensing Image Change Detection Based on Density Attraction and Multi-Scale and Multi-Feature Fusion

Qiuhan Jin; Yangping Wang; Jingyu Yang

doi:10.3788/LOP56.121003

Laser & Optoelectronics Progress, Volume. 56, Issue 12, 121003(2019)

Remote Sensing Image Change Detection Based on Density Attraction and Multi-Scale and Multi-Feature Fusion

Qiuhan Jin^1,2、*, Yangping Wang^1,2、**, and Jingyu Yang^1,2、***

Author Affiliations

¹ School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China

² Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China;

show less

Abstract Get PDF(in Chinese)

References(19)

[1] Du P J, Liu S C, Zheng H. Land cover change detection over mining areas based on support vector machine[J]. Journal of China University of Mining & Technology, 41, 262-267(2012).

[2] Li L, Shu N, Wang K et al. Change detection method for remote sensing images based on multi-features fusion[J]. Acta Geodaetica et Cartographica Sinica, 43, 945-953, 959(2014).

[3] Jia L, Li M, Wu Y et al. Semisupervised SAR image change detection using a cluster-neighborhood kernel[J]. IEEE Geoscience and Remote Sensing Letters, 11, 1443-1447(2014). http://ieeexplore.ieee.org/document/6722933/

[4] Wang G H, Li J L, Wang H B et al. Change detection based on adaptive fusion of multiple features[J]. Remote Sensing for Land & Resources, 30, 93-99(2018).

[5] Du P J, Liu S C. Change detection from multi-temporal remote sensing images by integrating multiple features[J]. Journal of Remote Sensing, 16, 663-677(2012).

[6] Zhao M, Zhao Y D. Object-oriented and multi-feature hierarchical change detection based on CVA for high-resolution remote sensing imagery[J]. Journal of Remote Sensing, 22, 119-131(2018).

[7] Tong G F, Li Y, Ding W L et al. Review of remote sensing image change detection[J]. Journal of Image and Graphics, 20, 1561-1571(2015).

[8] Hao M, Zhang H, Shi W Z et al. Unsupervised change detection using fuzzy c-means and MRF from remotely sensed images[J]. Remote Sensing Letters, 4, 1185-1194(2013). http://www.tandfonline.com/doi/full/10.1080/2150704X.2013.858841

[9] He P F, Shi W Z, Miao Z L et al. Advanced Markov random field model based on local uncertainty for unsupervised change detection[J]. Remote Sensing Letters, 6, 667-676(2015). http://www.tandfonline.com/doi/full/10.1080/2150704X.2015.1054045

[10] Niu P H, Li W H, Li X C. Remote sensing image change detection based on greedy EM algorithm for HMRF[J]. Opto-Electronic Engineering, 38, 50-56(2011).

[11] Tso B, Olsen R C. A contextual classification scheme based on MRF model with improved parameter estimation and multiscale fuzzy line process[J]. Remote Sensing of Environment, 97, 127-136(2005). http://www.sciencedirect.com/science/article/pii/S0034425705001458

[12] Wang D X, Li Y. The hyperspectral image classification method based on improved Markov model[J]. Information & Communications, 29, 16-17(2016).

[13] Zhang Q, Zhang L P, Huang X. Classification of high-spatial resolution imagery based on distance-weighted Markov random field with an improved iterated conditional mode method[J]. International Journal of Remote Sensing, 32, 9843-9868(2011). http://www.tandfonline.com/doi/full/10.1080/01431161.2010.549854

[14] Peng Y F, Song X N, Zi L L et al. Remote sensing image retrieval based on convolutional neural network and modified fuzzy C-means[J]. Laser & Optoelectronics Progress, 55, 091008(2018).

[15] Zhang Q C, Tong G F, Li Y et al. River detection in remote sensing images based on multi-feature fusion and soft voting[J]. Acta Optica Sinica, 38, 0628002(2018).

[16] Ye Z, Bai L, Nian Y J. Hyperspectral image classification algorithm based on Gabor feature and locality-preserving dimensionality reduction[J]. Acta Optica Sinica, 36, 1028003(2016).

[17] Li Z X, Shi W Z, Zhang H et al. Change detection based on Gabor wavelet features for very high resolution remote sensing images[J]. IEEE Geoscience and Remote Sensing Letters, 14, 783-787(2017). http://ieeexplore.ieee.org/document/7888966/

[18] Zhang H, Shi W Z, Wang Y J et al. Spatial-attraction-based Markov random field approach for classification of high spatial resolution multispectral imagery[J]. IEEE Geoscience and Remote Sensing Letters, 11, 489-493(2014). http://ieeexplore.ieee.org/document/6588895/

[19] Wen X F, Yang Z C, Chen M. Density attraction clustering algorithm between data points[J]. Journal of Frontiers of Computer Science and Technology, 12, 1996-2006(2018).

Tools

Get Citation

Copy Citation Text

Qiuhan Jin, Yangping Wang, Jingyu Yang. Remote Sensing Image Change Detection Based on Density Attraction and Multi-Scale and Multi-Feature Fusion[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121003

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Image Processing

Received: Nov. 26, 2018

Accepted: Jan. 11, 2019

Published Online: Jun. 13, 2019

The Author Email: Qiuhan Jin (18298378747@163.com), Yangping Wang (wangyp@mail.lzjtu.cn), Jingyu Yang (yangjy@mail.lzjtu.cn)

DOI:10.3788/LOP56.121003

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology