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Active contour for noisy image segmentation based on contourlet transform

[+] Author Affiliations
Da Chen

Shandong University, School of Information Science and Engineering, No. 27, Shanda South Road,Jinan 250100 China

Dengwang Li

Shandong Normal University, College of Physics and Electronics, 88 East Wenhua Road,Jinan 250014 China

Mingqiang Yang

Shandong University, School of Information Science and Engineering, No. 27, Shanda South Road,Jinan 250100 China

J. Electron. Imaging. 21(1), 013009 (Mar 12, 2012). doi:10.1117/1.JEI.21.1.013009
History: Received April 14, 2011; Revised November 8, 2011; Accepted November 14, 2011
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Abstract.  Active contour is one of the most successful variational models in image segmentation, pattern analysis, and computer vision. However, traditional active contour models not only require much expensive computation but are very sensitive to noise. We propose a scheme for noisy image segmentation integrating the active contour model with the contourlet transform, an optimal sparse representation of an image. Having reconstructed all the scale maps, we downsample the last but one scale map twice. Then, we apply the active contour model on the coarsest scale map and take the segmentation results as the initial curves for the finer scale map. Experiments have demonstrated that our proposed method can yield desired segmentation results both in real and synthetic images.

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Citation

Da Chen ; Dengwang Li and Mingqiang Yang
"Active contour for noisy image segmentation based on contourlet transform", J. Electron. Imaging. 21(1), 013009 (Mar 12, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.1.013009


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