A Photographer’s Guide to Color Histogram

Pixel Magazine
Jan 15, 2017 · 6 min read

This is Part 3 of a series on popular photographer tools by Polarr Photo Editor. Read Part 2 here.

Welcome back! Let’s talk about Histogram, a popular concept in photography and how to make a estimate about a picture’s exposure.

What is a histogram?

You can often find a little rectangle filled with red, green. blue and sometimes white bars and contours in photo editing software. This rectangle in the upper right corner of below picture is commonly referred as the histogram (see below).

All screenshots in this tutorial are taken in Polarr Photo Editor

Most histograms used in photography have two axes (high-five to those who still remember high school math). The horizontal axis represents brightness. From left to right, brightness is becoming higher and higher.

The vertical axis stands for pixel amount. From the bottom up, there are more and more pixels.

Therefore, the higher in the vertical axis (or convexities, in math term) of the histogram is in a certain brightness interval, the more pixels there exist in this interval. Take above histogram as an example. Most of its convexities stay on the left side, which indicates that, the picture’s overall brightness is relatively low.

Similarly, a “peak” in the middle implies more pixels of mid key (or not so bright nor so dark areas, thus “mid key”), and a “peak” on the right proves that there are more pixels in the bright area (or “high key”).

Now, why there are red, blue, green areas in the histogram? (as below picture shows). What do they refer to separately?

The colorful parts of a histogram is called the channel histogram, which includes three types — red, green and blue. Each type explains the distribution of pixels in this channel. The magenta, yellow, cyan colors are just the results of the overlap among red, green and blue channel histograms (An overlap of red and green produces yellow, an overlap of green and blue leads to cyan, and red and blue makes magenta). The white area is produced by the overlap of all the three channels.

In a black and white photo, because the three channels of a black-and-white photo are exactly the same in order to produce a gray scale image, you can only see white areas in the histogram (see below).

What are the different regions of a histogram called?

The parts and regions of Histograms of most pictures can be classified under five categories, which are low key, mid key, high key, low contrast and high contrast. We briefly mentioned these concept previously, now let’s look more into the details.

  1. Low key

As we can see from above picture, most pixels in this histogram gather on the left side, that is, the peak value occurs on the left extremity. However, there are no convexities on the right. And most parts of the picture are shadows. As a result, this is a picture of “low key” or “dark key”.

2. High key

What corresponds to low key oppositely are pictures of high key — most of the pixels gather on the right side (as seen above), and there are almost no pixels on the left. Such pictures are pictures of “high key” or “bright key”.

3. Mid key

The majority of images you take might have convexities of their histograms evenly distributed across different brightness intervals. Above is a picture and its mid key in the histogram, and that’s what most histograms with a balanced exposure should look like.

4. High contrast

High contrast histogram is also very typical. Most of its pixels are at the ends, and the peak value occurs on both the left and the right extremities. The large areas of highlights and shadows strikingly contrast with each other, and bring about a strong visual impact (see above example).

5. Low contrast

In contrast, this picture’s pixels are mainly concentrated in the center of the histogram, and both ends of the histogram don’t have any pixels. Overall, this is a picture of low contrast. Or generally speaking, it’s a very “grayish” picture with a weak visual impact.

How to make use of histogram — an example

Below is a picture with a good exposure. As what can be seen from the histogram, its pixels are evenly spread across shadows, mid key and highlights areas:

When we increase the exposure value, the contours in the histogram moves to the right, and this picture becomes a picture of high key.

When we decrease the exposure value, the contours in the histogram moves to the left, pixels gather on the left side, and this picture becomes a picture of low key.

When we increase the contrast value, the histogram’s distribution moves outwards to both ends, and two peaks sit separately on the left and the right extremities. This picture becomes a picture of high contrast after this adjustment.

When we decrease the contrast value, the histogram’s distribution moves inwards. Most peaks are in the middle part, which makes the picture a picture of low contrast.

Estimate exposure quality with histogram

A “good” or balanced histogram satisfies several requirements:

  1. There is no massive overflow of the contours near the left or right edges of the histogram, which means that, the contours are contained within the histogram. If you see the contours extend well beyond the left or right edges, it means there are lots of pure black (under exposure) and pure white pixels (over exposure).
  2. There are pixels in each brightness interval. A picture like this feels “richer” in color and has a more smooth transition among tones which is not abrupt or sudden.

3. A picture will have a better contrast and a more impressive visual effect if the ends are higher and the middle is lower in the histogram.

Of course none of the above requirements are necessary to produce a stunning photo. These are guidelines to provide you a quick understanding about the exposure level of the image.

Estimate color distribution with histogram

Now that you’ve become an expert in histogram, it’s not hard to see that we can easily estimate a picture’s color distributions through histogram just by looking at the area of colors in the histogram.

Take the above picture as an example. The red channel mainly stays in the highlights area, and most areas of red channel are on the right side of the histogram. This indicates that, the brighter area of the photo is largely consist of red colors. We can say, the dominant highlight color of this image tends to be red.

This marks the end of this episode of our Photographer’s guide. See you soon next time and receive update by following Pixel Magazine.

Want to try this out yourself? Download Polarr Photo Editor here. Polarr is available on iOS, Android, Mac, Windows, Chrome, and even online!

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A celebration of photography and art brought to you by Polarr. https://www.polarr.co.

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