灰度共生矩阵// Python
[英]Grey Level Co-Occurrence Matrix // Python
问题描述
I am trying to find the GLCM of an image using greycomatrix from skimage library. 
我正在尝试使用skimage库中的greycomatrix查找图像的GLCM。 I am having issues with the selection of levels. 我在选择级别时遇到问题。 Since it's an 8-bit image, the obvious selection should be 256; 由于它是8位图像，因此显而易见的选择应该是256；否则，它应该是256。 however, if I select values such as 8 (for the purpose of binning and to prevent sparse matrices from forming), I am getting errors. 但是，如果我选择诸如8之类的值（出于合并目的并防止形成稀疏矩阵），则会出现错误。
QUESTIONS: 问题：
- Does anyone know why? 有人知道为什么吗？
- Can anyone suggest any ideas of binning these values into a 8x8 matrix instead of a 256x256 one? 谁能提出将这些值合并到8x8矩阵而不是256x256矩阵中的想法？
1 个解决方案
解决方案1
2 已采纳 2016-07-11 01:13:06
The simplest way for binning 8-bits images is to divide each value by 32. Then each pixel value is going to be in [0,8[. 合并8位图像的最简单方法是将每个值除以32。然后每个像素值将在[0,8 [。
Btw, more than avoiding sparse matrices (which are not really an issue), binning makes the GLCM more robust to noise. 顺便说一句，比避免稀疏矩阵（这不是真正的问题），分箱使GLCM对噪声更鲁棒。
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