Optical aerial image partitioning using level sets based on modified Chan-Vese model

Authors:
Guo Cao;Zhihong Mao;Xin Yang;Deshen Xia
Affiliations:
The School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China;Computer Science Department, Sun Yat-sen University, Guangzhou 510275, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China;The School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

We propose an optical aerial image partitioning method using level set evolution for an arbitrary number of regions and embark on the concept of using one level set function for each region in this paper. The proposed method can be viewed as an extension of the Chan-Vese 2-phase segmentation model. Texture features derived from wavelet transform are utilized to characterize each class in the proposed method. Unlike most of the previous works, the curve evolution partial differential equations for different level set equations are decoupled. Each region of class evolves according to its features and interacts with the neighbor regions in order to obtain a partition with regular contours. Generally, the proposed algorithm is easy to implement and appears to converge in fewer iterations. Results are shown on both synthetic and real images.