Laser & Optoelectronics Progress, Volume. 53, Issue 11, 112801(2016)
Remote Sensing Image Segmentation Based on Fractal Net Evolution Approach and Improved Fuzzy C-Means
[1] [1] Zheng Yuyong. Object-oriented research of road extraction from high-resolution remotesensing image[D]. Wuhan: Huazhong University of Science and Technology, 2014.
[2] [2] Wang Yan, Wang Xiaoqing, Dou Aixia. Building damage detection of the 2008 Wenchuan China earthquake based on object-oriented classification method[J]. Earthquake, 2009, 29(3): 54-60.
[3] [3] Cui W, Zhang Y. An effective graph-based hierarchy image segmentation[J]. Intelligent Automation and Soft Computing, 2011, 20(7): 969-981.
[4] [4] He Min, Zhang Wenjun, Wang Weihong. Optimal segmentation scale model based on object-oriented analysis method[J]. Journal of Geodesy and Geodynamics, 2009, 29(1): 106-109.
[5] [5] Li Qin, Gao Xizhang, Zhang Tao, et al. Optimal segmentation scale selection and evaluation for multi-layer image recognition and classification[J]. Journal of Geo-Information Science, 2011, 13(3): 409-420.
[6] [6] Gong Qu, Yao Yumin. Image segmentation based on watershed and improved fuzzy c-means clustering[J]. Application Research of Computers, 2011, 28(12): 4773-4775.
[7] [7] Zhang H, Fritts E J, Goldman S A. Image segmentation evaluation: A survey of unsupervised methods[J]. Computer Vision and Image Understanding, 2008, 110(2): 260-280.
[8] [8] Espindola G M, Camara G, Reis I A, et al. Parameter selection for region-growing image segmentation algorithms using spatial autocorrelation[J]. International Journal of Remote Sensing, 2006, 27(14): 3035-3040.
Get Citation
Copy Citation Text
Wang Min, Song Zhengfu, Wang Zhihui. Remote Sensing Image Segmentation Based on Fractal Net Evolution Approach and Improved Fuzzy C-Means[J]. Laser & Optoelectronics Progress, 2016, 53(11): 112801
Category: Remote Sensing and Sensors
Received: May. 30, 2016
Accepted: --
Published Online: Nov. 14, 2016
The Author Email: Min Wang (1597825503@qq.com)