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fenshuiling1

于 2019-03-18 发布
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说明:  基于标记的分水岭算法,弥补了传统分水岭算法存在的过分割问题。(Marker-based watershed algorithm makes up for the over-segmentation problem of traditional watershed algorithm.)

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fenshuiling1.m, 1510 , 2019-03-15

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    针对分水岭算法存在的过分割问题以及VCH-F1切片图像的特点,提出一种能够有效消除局部极小值和噪声干扰的自动分割方法。首先比较彩色分量梯度图,选择分量图像的梯度信息,达到有效提取图像边缘信息的目的;然后提出基于多阈值分割的方法消除无效梯度信息;最后介绍了算法的步骤及结果。实验结果证明,通过该方法处理的梯度图像再进行分水岭算法处理,即使不进行区域合并也能达到很好的效果。(Watershed algorithm for over-segmentation problem of the existence of VCH-F1 as well as the characteristics of the image slice, a can effectively eliminate the local minimum value and noise automatic segmentation method. Comparing the first color component gradient map, select the quantity of image gradient information, achieve an effective extraction of image edge information purposes then made based on multi-threshold segmentation method to eliminate invalid gradient information Finally introduce the steps of the algorithm and results. Experimental results show that the adoption of the method of treatment of gradient watershed algorithm for image re-treatment, even if there is no regional merger will also achieve good results.)
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    图像预处理:分水岭分割算法,图像灰度化、高斯平滑、均衡直方图、图像对比度增强(Image Pre-processing: a watershed segmentation algorithm, images of gray-scale, Gaussian smoothing, balanced histogram, image contrast enhancement)
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    说明:  多尺度分水岭变换分割图像,利用此编码可以编程计算在不同程度有效分割图像。(Image Segmentation)
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