| 摘要: |
| 本文研究了基于小波分析改进的C-V 模型图像分割问题. 利用小波多分辨率分析和改进的窄带水平集方法, 获得了比传统C-V 模型分割速度更快、准确度更高、算法复杂度更低的分割结果. 推广了C-V 水平集模型如何快速准确地分割灰度不均匀的图像和窄带水平集法等结果. |
| 关键词: 图像分割 C-V水平集 小波变换 窄带法 |
| DOI： |
| 分类号:O29 |
| 基金项目: |
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| THE IMPROVED C-V LEVEL SET IMAGE SEGMENTATION MODEL BASED ON WAVELET ANALYSIS AND NARROW BAND |
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FU Jin-ming1,2, YI Xu-ming2
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1.School of Science, Huazhong Agricultural University, Wuhan 430070, China;2.School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
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| Abstract: |
| In this paper, we study the problem of image segmentation of C-V model. By using the wavelet transform and the improved level set and narrow band method, image edge information and the initial segmentation curve are obtained. We get a segmentation result which is faster in segmentation speed, higher in accuracy and lower in algorithm complexity than traditional C-V model. The results of the C-V level set model for the segmentation of gray uneven images and the initialization of the zero level set and the narrow band method are generalized. |
| Key words: image segmentation C-V level set wavelet transform narrow band method |
