首页> 外文会议>International Conference on Signal Processing(ICSP'06); 20061116-20; Guilin(CN) >Watershed Segmentation Based on Multiscale Morphological Fusion
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Watershed Segmentation Based on Multiscale Morphological Fusion

机译:基于多尺度形态学融合的流域分割

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Image segmentation based on watershed method always results in over-segmentation. To alleviate this problem, watershed segmentation based on multiscale morphological fusion is presented. The target image is filtered with multiscale structure element and many result images are obtained with the parallel processing. This paper does image fusion using wavelet transform and choose the fusion principles respectively for high frequency and low frequency coefficients. This algorithm can eliminate the noise while preserving the main contour of target. Then this paper adopts image maximum entropy to determine the initial threshold of watershed. Lastly, an effective region merging algorithm is proposed to improve segmentation result. Experiments show that the proposed algorithm is efficient.
机译:基于分水岭方法的图像分割总是导致过度分割。为了缓解这一问题,提出了基于多尺度形态学融合的分水岭分割方法。使用多尺度结构元素对目标图像进行滤波,并通过并行处理获得许多结果图像。本文利用小波变换进行图像融合,分别针对高频系数和低频系数选择融合原理。该算法可以在保持目标主轮廓的同时消除噪声。然后采用图像最大熵确定流域的初始阈值。最后,提出了一种有效的区域合并算法以提高分割效果。实验表明,该算法是有效的。

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