Robust image segmentation via Bayesian type criterion |
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Authors: | Xiaoguang Wang Dawei Lu Lixin Song |
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Institution: | 1. School of Mathematical Sciences, Dalian University of Technology, Dalian, Liaoning, Chinawangxg@dlut.edu.cn;3. School of Mathematical Sciences, Dalian University of Technology, Dalian, Liaoning, China |
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Abstract: | Image segmentation plays an important role in image processing before image recognition or compression. Many segmentation solutions follow the information theoretic criteria and often have excellent results; however, they are not robust to reduce the noise effect in contaminated image data. To guarantee the optimal segmentation with possible noise, a robust Bayesian information criterion is proposed to segment a grayscale image and it is less sensitive to noise. The asymptotic properties are also studied. Monte Carlo numerical experiments along with a brain magnetic resonance image are conducted to evaluate the performance of the new method. |
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Keywords: | Bayesian information criterion image segmentation model selection consistency noisy image robust estimation |
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