使用Ruby和imagemagick获取或计算图像的熵 [英] Get, or calculate the entropy of an image with Ruby and imagemagick

问题描述

如何在Ruby中找到imagemagick的entropy，最好是mini_magic？我需要这个作为更大项目的一部分，在图像中找到兴趣，以便裁剪。

How to find the "entropy" with imagemagick, preferably mini_magic, in Ruby? I need this as part of a larger project, finding "interestingness" in an image so to crop it.

我找到了一个好的 Python / Django中的示例，它提供以下伪代码：

I found a good example in Python/Django, which gives the following pseudo-code:

image = Image.open('example.png')
histogram = image.histogram() # Fetch a list of pixel counts, one for each pixel value in the source image

#Normalize, or average the result.
for each histogram as pixel
  histogram_recalc << pixel / histogram.size
endfor

#Place the pixels on a logarithmic scale, to enhance the result.
for each histogram_recalc as pixel
  if pixel != 0
    entropy_list << log2(pixel)
  endif
endfor

#Calculate the total of the enhanced pixel-values and invert(?) that.
entropy = entroy_list.sum * -1

这将转换为公式 entropy = -sum（p。* log2（p））。

我的问题：我是否正确解释了Django / Python代码？如果有的话，我如何在ruby的mini_magick中获取直方图？

My questions: Did I interprete the Django/Python code correct? How can I fetch a histogram in ruby's mini_magick if at all?

最重要的问题：首先这个算法有什么好处吗？你会建议一个更好的人来找到（部分）图像中的熵或变化像素量或渐变深度吗？

Most important question: is this algorithm any good in the first place? Would you suggest a better one to find the "entropy" or "amount of changing pixels" or "gradient depth" in (parts of) images?

编辑：使用a.o.下面的答案提供的资源，我想出了工作代码：

Edit: Using a.o. the resources provided by the answer below, I came up with the working code:

# Compute the entropy of an image slice.
def entropy_slice(image_data, x, y, width, height)
  slice = image_data.crop(x, y, width, height)
  entropy = entropy(slice)
end

# Compute the entropy of an image, defined as -sum(p.*log2(p)).
# Note: instead of log2, only available in ruby > 1.9, we use
# log(p)/log(2). which has the same effect.
def entropy(image_slice)
  hist = image_slice.color_histogram
  hist_size = hist.values.inject{|sum,x| sum ? sum + x : x }.to_f

  entropy = 0
  hist.values.each do |h|
    p = h.to_f / hist_size
    entropy += (p * (Math.log(p)/Math.log(2))) if p != 0
  end
  return entropy * -1
end

其中image_data是 RMagick ::图片。

Where image_data is an RMagick::Image.

这用于 smartcropper gem ，它允许用例如智能切片和裁剪图像回形针。

This is used in the smartcropper gem, which allows smart slicing and cropping for images with e.g. paperclip.

推荐答案

这里解释了熵（使用MATLAB源代码，但希望定性解释有帮助）：

Entropy is explained here (with MATLAB source, but hopefully the qualitative explanation helps):

Entropy简介（MATLAB中的数据挖掘） ）

有关更正式的解释，请参阅：

For a more formal explanation, see:

信息理论要素（第2章），封面和托马斯

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