How to interpret and use photography histograms

Oct 10, 2018 by Michel Garofano
14 MIN


The histogram is a tool that allows one to analyze the content of an image and to interpret the desired rendering. 

- At the shoot, to know if the exposure is correct

- While processing the image to adjust contrast and brightness

The histogram counts each light point and creates a two-axis table

How to use histogram

Image credit Michel Garofano

The X axis, the most important, ranges from 0% to 100% brightness. The Y axis indicates the number of pixels for each value. 

Note that some manufacturers present colour histograms but the principle remains the same.

colored histogram photo

To facilitate the understanding, I chose to photograph a test pattern with 3 levels of grey.

Using histogram

Image credit Michel Garofano

Each zone being almost homogeneous, I clearly find the 3 zones on my graph

Shooting Use

Viewing the images on the camera's rear screen simply determines the content and framing. In no case can the exposure be judged. The histogram is the only arbiter.

Ideally, the ends of the curve should be visible for maximum nuance.

Using histogram for the first time

Image credit Michel Garofano

When the histogram is moved to the right (overexposed), I have more details in the dark parts but I compress all the light parts, I lose some nuances. Inversely if I move the histogram to the left by underexposing. The image of the environment is therefore well exposed.

Example with a street scene in cloudy weather. That is, a whole range of grey without really deep blacks or pure whites except for the sky triangle at the top left.

Starting to use histogram

Image credit Michel Garofano

- My shades of grey are well represented in the center of the histogram.

- I recorded every detail from the darkest to the brightest

- The slopes of the curve are not steep, the image is soft

- At the right end I find a point corresponding to the sky

Here is the difference with an underexposed 2 f-stops image

Histogram for people just starting up

Image credit Michel Garofano

- My scene is grey but the maximum of my histogram is on the left, towards black.

Here is the difference with an overexposed 2 f-stops image

Histogram for people beginning

Image credit Michel Garofano

The medium greys are mainly in the light part and above all the slope towards the white has been truncated. I have lost all the light shades, they have become white.

If you have understood the principle, I suggest you analyze the histogram of this image:

Histogram with horses

Image credit Michel Garofano

The main subject is the horse. It is white and I will be very careful not to lose information in the clearest parts of the image. After shooting I look at the histogram at the back of the camera:

histogram photography


  • On the right, I see that the white is not burnt but the inclination is steep
  • The field that composes the majority of the image is in mid-greys.
  • The shadow is not black but dark grey

Conclusion, for the dark I have some margin, if I under-expose by 1/2 EV, I will accentuate the details on the horse, the slope of the whites will then be more nuanced, less steep.

My histogram will be different if my subject is a coal pile or a snowman, so you must learn to interpret the histogram according to the subject.


- For energy and calculation time saving, your device determines the histogram by random sampling. It does not fully count the pixels present.  

- Depending on your camera, it is possible to make the over or underexposed areas blink. Beware, this function is more or less precise and sometimes troublesome.

- A few years ago, a polemic arose over the " right exposure," that is to say, that the clearest part of the scene was at the limit of 100%. If the mathematical explanation is logical, the photographic rendering is much less so.  

In processing:

The principle is the same as for shooting: if we want to keep as many shades as possible, the histogram must be well balanced so as not to clip either the blacks or the whites.

Histogram in processing

Image credit Michel Garofano

If we make a correction to the image above, we will have to check that we are not losing information. Below, the blacks are cut and we don't have any whites

How to process photos in histogram

Image credit Michel Garofano

On the other hand, if we over lighten the file, the whites are clipped, the light shades are compressed, the photo is less nuanced.

Histogram processing

Image credit Michel Garofano

Note that some software allows you to control clipped areas by displaying color swatches. For example, with Lightroom, you must click on the tips of the histogram to make visible the parts that are too dark or too bright.

How to process histogram photo

Image credit Michel Garofano


DEFINITION: In retouching, we talk about levels. The principle and graph are identical to the histogram. In short, the levels are histograms on which we can intervene.

Programmers have been inspired by argentic development to create their software. For this reason, we can find the brightness/contrast function
levels histogram

Image credit Phenix Photos

"Brightness" is the equivalent of the exposure time under the magnifier

"Contrast" corresponds to the grade of paper used

The same is obtained with the levels. In addition, we have perfect control over where blacks start and whites end. The 2 most useful tools in an editor are therefore levels and curves.

histogram brightness histogram

Image Credit Stéphane Peres

When we bring the ends of the levels together, we increase the contrast because all the tones in the image are concentrated on a narrower range: the transitions between these tones will, therefore, be faster (the very notion of contrast).  Moving the grey cursor darkens or brightens the image (Gamma is modified, which is equivalent to the transition speed between dark and light tones, so with a similar effect, a sensation of increasing contrast).

For the demonstration, let's return the grey chart previously used and add 3 control squares (White 100%, grey 50%, black 0%) that will not undergo any changes during the settings.

Histogram control squares

Image credit Michel Garofano

If we want the medium grey to be at 50% brightness, we will move the grey cursor under the concerned part of the histogram  

Histogram brightness

Image credit Michel Garofano

I brightened the whole image without changing its contrast. If, on the other hand, we want light grey to be 100% white and dark grey to be 0% black, we will move the appropriate cursors.

Histogram personalising brightness

Image credit Michel Garofano

The contrast of the image has just been increased without changing the medium grey. By the way, we lost all the nuances of the extremities. We "cut" (clipped) the blacks and whites

Case study:

The rescue of a poorly exposed image can only be done properly with a RAW file. The JPG format will degrade the image (see explanation below).

Let's imagine that this image has been overexposed but we like it very much and therefore want to improve it:

Histogram pink flower

Image credit Michel Garofano

By moving the black cursor, we will look for the darkest area. By moving the grey cursor, we will darken the image

Histogram pink flower case study

Image credit Michel Garofano

Note that the burned areas will remain white without any details whatever we do (as explained above).

RAW versus JPG:

During the shooting I chose to save the images in RAW+JPEG fine.

Histogram RAW vs JPG

Histogram RAW

Image credit Michel Garofano

If you apply the same correction to the JPG, after the setting, the histogram is damaged:

Histogram JPG

Image credit Michel Garofano

The graph is not continuous, there are "holes".

This is referred to as a "comb histogram". The light parts have been stretched so much towards the dark that information in the light colours is missing. Details are lost, gradients are not respected. If the example is not visually very clear here because of JPEG compression for web publishing, it will be much more obvious on a print run.

Correction by layer:

I took the picture below in mid-morning but the result is not true to the scene I witnessed. The image is too soft and much too red. We will use the levels to correct the image.

Histogram correction

Image credit Michel Garofano

To gain in contrast, we will move the cursors onto the first black pixels and the last white ones.

Histogram correction gain contrast

Image credit Michel Garofano

Then, on the red layer, we move the cursor in order to lighten it.

Histogram contrast red layer

Image credit Michel Garofano

In case you are still not satisfied, we can continue the processing by playing with the contrast of the red, green and blue layers:

Histogram processing continued

Image credit Michel Garofano

Histogram processing green

Image credit Michel Garofano

Histogram processing blue

Image credit Michel Garofano

... and here's the result! It seems much more in keeping with what I saw that morning:

Histogram post-production

Image credit Michel Garofano


When shooting, it seems essential to me to know this tool and to master it in order to choose the correct exposure in difficult cases. During processing, it is important to check what details you may lose.

I hope I've convinced you to use the histogram more often!

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