文件名称:Watershed-Based-Segmentation-
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- 2014-05-09
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图像分割是一种重要的图像分析技术,对图像分割的研究一直是图像技术研究中的热点和焦点。分水岭算法是基于数学形态学理论的图像分割算法,但是对噪声敏感且存在过分割的现象。为提高图像分割效果,本文通过对影像进行滤波处理,用改进的快速区域合并算法优化分水岭算法进行影像分割。实验结果与MeanShift算法得到的结果对比,证明此算法可以获得较好的分割效果。-In recent years, the watershed line has emerged as the primary tool of mathematical
morphology for image segmentation. Several very efficient algorithms have been
devised for the determination of watersheds. Nevertheless, the application of watershed
algorithms to an image is often disappointing: the image is oversegmented into
a large number of tiny, shallow watersheds, where one wanted to obtain only a few
deep ones. This paper presents a novel approach to watershed merging. Mainly, it
addresses the following question: given an image, what is the closest image that has
a simpler watershed structure? The basic idea is to replicate the process of watershed
merging that takes place when rain falls over a real landscape: smaller watersheds
progressively fill until an overflow occurs.
morphology for image segmentation. Several very efficient algorithms have been
devised for the determination of watersheds. Nevertheless, the application of watershed
algorithms to an image is often disappointing: the image is oversegmented into
a large number of tiny, shallow watersheds, where one wanted to obtain only a few
deep ones. This paper presents a novel approach to watershed merging. Mainly, it
addresses the following question: given an image, what is the closest image that has
a simpler watershed structure? The basic idea is to replicate the process of watershed
merging that takes place when rain falls over a real landscape: smaller watersheds
progressively fill until an overflow occurs.
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