What is the color structure histogram and how does it work

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    \$\begingroup\$ You have just repeated yourself in the body / title. Please edit to explain a) why you want to know b) what you have tried to find this out and c) is there an alternate wording for new users trying to find this question? \$\endgroup\$
    – Tim
    Jan 8, 2015 at 20:57
  • \$\begingroup\$ Do you mean the RGB histogram? photo.stackexchange.com/questions/22097/… \$\endgroup\$
    – MikeW
    Jan 8, 2015 at 21:14
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    \$\begingroup\$ This is an image processing term. It is not typically relevant in photography. To be more clear — this is not the same thing as a normal color histogram or an RGB histogram. Its main use is in image searching. I am not, however, voting to close, because it's possible that there's some practical post-processing use that I'm not aware of. \$\endgroup\$
    – mattdm
    Jan 9, 2015 at 2:16
  • \$\begingroup\$ Google turns up details including this page: quora.com/… \$\endgroup\$
    – JDługosz
    Jan 10, 2015 at 8:02
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    \$\begingroup\$ Since the quara site has an answer to the identical question, you should be more specific about what you are looking for. \$\endgroup\$
    – JDługosz
    Jan 10, 2015 at 22:35

2 Answers 2


A great answer to this question was posted on Quora by Kadir A. Peker:

Color structure histogram was proposed to alleviate the problem of the regular histogram that it reflects nothing of the spatial distribution of the colors in the image. That is, given a color histogram, the colors could be each lumped as blobs of colors, or they could be randomly distributed all over the image where each pixel is a different color; the color histogram will tell you nothing about this "structure".

The proposed histogram works as follows: You have a "structuring element", basically a kernel or a sliding window, that you slide over your image just like when filtering. At each position of the structuring element, you check whether color X appears in the window, and increment its bin value if it does. You do this for all colors in your histogram.

The effect of this process, i.e. using a window to count colors rather than counting them pixel by pixel is as follows: If a color is distributed all over the image, then each pixel of that color appears in a sliding window (many times actually, as the window slides over it) by itself. So, each single pixel contributes significantly. If, on the other hand, the color appears as a single blob in the image, then the pixels of that color count only as one in the bin when the sliding window is on top of them. So, in short, color structure histogram boosts the weight of a color in the histogram if that color is well distributed over the image rather than accumulated at a single location.

(FYI: Quora allows content to be reproduced on other sites, as long as you attribute the author properly)

There is also a good visualization of the scanning process in the following presentation:

enter image description here

  • \$\begingroup\$ re: your comment about Quora content: It's not clear Quora's TOS is compatible with CC BY-SA. Regardless, I applaud you acknowledging the TOS and the issue, and doing your level best to comply openly. =) \$\endgroup\$
    – scottbb
    Dec 24, 2017 at 16:27
  • \$\begingroup\$ Also regardless, for certain short citations, Fair Use probably applies in any case. I have no idea what the boundaries of "short citations" are, however. =\ \$\endgroup\$
    – scottbb
    Dec 24, 2017 at 16:29

You can display a histogram showing the distribution of values from black to white, or see it broken into the three colors, both within higher-end camera viewfinders while viewing the subject or immediately after taking the photo, and also in many image manipulation tools, such as Adobe Photoshop or the free IrfanView. This allows you to make exposure decisions and to alter the image to spread out the histogram or to make the image high key (distribution concentrated at the high end, e.g. for a face) or low key (dark, as for a silhouetted figure in an alley).

See http://www.cambridgeincolour.com/tutorials/histograms2.htm, http://www.nobadfoto.com/histogram-2.html


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