Histogram 101

Written by:


Stated simply, a histogram is general overview of the how light or dark the different tonal values are in your photo. To make sense of this we have to look at each part of the histogram. The photo below was taken right of a camera’s LCD showing a histogram.

The x-axis or the horizontal line represents the total number of tones your camera can record. In a regular 8-bit JPG there are about 255 levels of brightness ranging from pure black to pure white. These 255 levels are then further divided into 5 sections as seen in the histogram photo above. These five sections represent the 5 f-stop range that modern day DSLRs can record. The leftmost part of the x-axis is where the darker tones are located. The midpoint represents 18% gray which is neutral, while the rightmost part is where the highlights are. If the graph overflows to either the right or the left side of x-axis then it means you’ve lost some detail in either the highlights or shadows respectively since you’re already going over the recording capability or dynamic range of your camera. This is known as clipping.

The y-axis or vertical line represents how much information is contained in a given tonal value. The higher the graph, the more information is at that given point.


The most common use of the histogram is to check whether or not you’ve clipped the highlights or shadow areas of your photo.

The photo above is the LCD of my camera after I took a shot of a figurine inside a book case. There was minimal light in the scene and the background was mostly covered in shadow. Since I was shooting in manual mode, I used the histogram to check if I lost any detail in the shadows. Since the leftmost part of the graph ended before reaching the edge, I know that I didn’t lose any shadow detail.

If the histogram of the photo was like the one below then I know that I’ve lost a lot of data in the shadows. The important thing to remember is that the higher the graph that falls off the edge of the x-axis, the more data you’re losing.


The RGB histogram is a more precise way of looking at the data in your photo. Like the name states, you get a histogram for the red, green and blue channels separately. What most beginners don’t know is that when you look at the “regular” single histogram you’re not looking at the average of the RGB channels but only the green channel. Below is the RGB histogram of the same photo used above.

If you look closely, you can see that the single histogram at the bottom right of the LCD approximates the green channel histogram. You can try this yourself. What this means is that you can actually be losing detail in the red and blue channels and not know it if you’re only looking at the single histogram. It’s best to have your camera default to showing you an RGB histogram if it’s available.


Looking at the image preview of your camera’s LCD will not tell you how bright or dark the image is. This is because the brightness level of the LCD depends on ambient light. Try looking at your LCD in under the sun and everything looks dark while the same image will look brighter if you’re in complete darkness. The histogram will give you a quick overview of the overall brightness of the image, regardless of where you are, so you can re-shoot right away if you have to.

Most DSLRs also have a highlight alert feature where the clipped or blown highlights will blink during image preview. Unlike the histogram, it will only tell you about lost highlights and not lot shadow details.


I’ve heard a lot of photographers say that the histogram of a photo should approximate a bell curve or a normal distribution. The photo below shows a what a bell curve looks like.

In a bell curve, most of the data is located in the midtones while there is very little shadow or highlight data. This is a sweeping generalization. If you’re taking a photo composed mainly of midtones like foliage then of course the histogram will look like a bell curve. But what if you’re taking a photo of a very bright subject like say a snow covered terrain, would you still expect the histogram to look like a bell curve? Of course not.

The curve will be biased towards that right since the subject is mostly white. It’s the same thing when taking a photo of a a predominantly dark scene where the graph will be biased towards the left. If you re-adjust your settings to get a bell curve then you will be underexposing a bright scene or overexposing a dark one.

Histogram of image below

CC Photo by saital

The histogram only gives you a general overview. It does not show you all the data in your photo so you cannot base everything on it. Like we mentioned earlier, a histogram only represents around 256 tonal values that only represent brightness levels. If you add color to the equation then an 8-bit RGB jpeg has 16.7 million possible values. This is just one of the tools at your disposal in getting the shot right.

Related Reading:
Going Manual: Learning the Basics of Exposure
When to Use Exposure Compensation
Photography 101 Series

Previous Post:

Comments are closed.