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基于多尺度形态学融合的分水岭图像分割方法
引用本文:王鹏伟,吴秀清,张名成.基于多尺度形态学融合的分水岭图像分割方法[J].数据采集与处理,2006,21(4):398-402.
作者姓名:王鹏伟  吴秀清  张名成
作者单位:中国科学技术大学电子工程与信息科学系,合肥,230027
基金项目:国家高技术研究发展计划(863计划)
摘    要:提出了一种基于多尺度形态学融合的分水岭图像分割方法,采用多尺度结构元素对输入图像并行滤波,并对结果图像进行基于小波变换的图像信息融合。针对小波分解的不同频率域,选择不同的融合规则,既抑制噪声又保持目标轮廓信息。最后,采用最大熵法自适应确定算法的初始阈值,并给出一种有效的区域合并方法来优化分割结果。实验证明,采用此分割方法可以获得较好的分割结果。

关 键 词:分水岭  多尺度  小波变换  图像融合  图像分割
文章编号:1004-9037(2006)04-0398-05
收稿时间:2005-12-30
修稿时间:2006-08-27

Watershed Segmentation Based on Multiscale Morphological Fusion
Wang Pengwei,Wu Xiuqing,Zhang Mingcheng.Watershed Segmentation Based on Multiscale Morphological Fusion[J].Journal of Data Acquisition & Processing,2006,21(4):398-402.
Authors:Wang Pengwei  Wu Xiuqing  Zhang Mingcheng
Affiliation:Department of Electronic Engineering and Information Science,University of Science and Technology of China, Hefei, 230027, China
Abstract:The image segmentation based on the watershed method always results in over-segmentation. The novel watershed segmentation algorithm is proposed to solve this problem. The target image is filtered using multiscale structure element with the parallel processing. This paper presents the image fusion using the wavelet transform and chooses fusion principles, which can eliminate the noise while preserving the main contour of target. Finally, the image maximum entropy is adopted to determine the initial threshold of the watershed and segmentation results are improved by the effective region merging method. Experiments show that the proposed algorithm is efficient.
Keywords:watershed  multiscale  wavelet transform  image fusion  image segmentation
本文献已被 CNKI 维普 万方数据 等数据库收录!
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