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enfcm

于 2021-04-12 发布
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说明:  Szilagyi等人提出的EnFCM算法加快了灰度图像的聚类过程。通过对像素点及其8邻域像素的线性加权求和预处理原图像,形成了从原始图像到其局部的邻域像素的平均图像。由于像素的灰度级值一般是8位分辨率(256级灰度),M级灰度值的编码一般比像素点大小为N的值小很多。因此,执行时间明显减少。(The enfcm algorithm proposed by szilagyi et al. Accelerates the clustering process of gray images. Through the linear weighted sum of pixels and their 8 neighborhood pixels, the average image from the original image to its local neighborhood pixels is formed. Because the gray level value of a pixel is generally 8-bit resolution (256 gray level), the coding of M-level gray level value is generally much smaller than the value of pixel size n. As a result, execution time is significantly reduced.)

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enfcm.m, 3124 , 2020-05-22

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