要执行K均值聚类K = 3（段）。所以我：

To perform K means clustering with k = 3 (segments). So I:

1）转换的RGB IMG为灰度

1) Converted the RGB img into grayscale

2）铸造原始图像转换为X 1，列矩阵

2) Casted the original image into a n X 1, column matrix

3）IDX = k均值（column_matrix）

3) idx = kmeans(column_matrix)

4）输出= IDX，浇铸放回相同的尺寸与原始图像

4) output = idx, casted back into the same dimensions as the original image.

我的问题是：

A

当我这样做imshow（输出），我得到一个纯白色的图像。然而，当我这样做imshow（输出[0 5]），它显示了输出图像。我的理解是0和5指定显示范围。但是，为什么我必须这样做？

When I do imshow(output), I get a plain white image. However when I do imshow(output[0 5]), it shows the output image. I understand that 0 and 5 specify the display range. But why do I have to do this?

B） 现在的输出图像是指被划分成3个段权。我怎么门槛是这样的，我分配一个

B) Now the output image is meant to be split into 3 segments right. How do I threshold it such that I assign a

0为区域1的簇 1簇区域2的 2集群区域3

0 for the clusters of region 1 1 for clusters of region 2 2 for clusters of region 3

由于我的整点做这个集群是让我可以分割图像分为3个区域。

As the whole point of me doing this clustering is so that I can segment the image into 3 regions.

非常感谢。

亲切的问候。

推荐答案

答：考虑到你的矩阵输出包含标值范围从1 3， imshow（输出）被这当作一个的灰度的矩阵，假设全值范围是0到255这就是为什么制约了颜色限制是必要的，否则您的图像全白或几乎全白。

A: Given that your matrix output contains scalar values ranging from 1 to 3, imshow(output) is treating this as a grayscale matrix and assuming that the full range of values is 0 to 255. This is why constraining the color limits is necessary as otherwise your image is all white or almost all white.

B： 输出=输出 - 1