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Photography Basics: Understanding Histograms - Your Perfect Guide

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The tonal range present in any image can be summarized effectively using histograms that prove as a very useful tool offered by various cameras. It is a graphical representation of tones in the image arranged from black to white, going left to right. The height of the graph at any point indicates the density of pixels in that tone in the given image. Mostly all modern imaging software use histograms. Understanding histograms is, thus, vital.

Most digital cameras including the compact ones display histograms and some also offer the feature of live histogram viewing while shooting using the LCD screen. While understanding histograms appear pretty complex in the first instance, they are actually not. A basic understanding can help one employ them for photography needs.

Understanding Histograms

A histogram is basically a result of a lot of arithmetic and number play but luckily we as photographers need not be bothered about it. Numbers aren’t critical and hence are excluded from the graphs. The mathematical nitty-gritty of depth and dynamic ranges are inconsequential for photography.

Reading histograms though may seem intimidating but can be simplified by just considering histograms as graphs where the horizontal axis represents the luminance of the image and the y-axis represents the quantity of light relative to the luminance.
The major factors involved in understanding histograms are knowing the scene that is an idea of brightness, darkness or contrast of the subject to be photographed and the goal that is mostly a proper exposure that varies per photographer as everyone has a different vision of a perfect image.

Understanding Histograms

The above histogram can be divided into tones from left to right viz. blacks, shadows, mid-tones, highlights, whites based on the horizontal axis that goes from left to right as from deep black to pure white. Looking at the height of the plotted graph in a particular tone, one can know of the density of pixels in that tone.

The graph, for example, shows that there are maximum pixels in the white tone. In other words, it indicates the level of brightness of the image. The histogram is dependent majorly on exposure but also depends on tone curve and other settings.

The concept can be understood better by understanding the concept of the scene and goal.


A scene is basically what is being photographed and the histogram depends on it majorly. A large spike on the left of the graph can be observed if one is photographing a night scene or a subject in low light conditions.

Photographing the night sky, for instance, may show a great spike on the left side of histogram while photographing the sun may result in high frequencies on the right of the graph.

Understanding Histograms

The histogram here depends on the composition of the picture and that is the scene.


While a lot of us and photography literature is seen raving about the perfect exposure, it is good to know that there isn’t a thing called the perfect exposure as photography is art. It varies per photographer and viewer as to what they deem perfect.

Overexposure or underexposure may be intended and achieving that is a perfect setting in the context.

Histograms can hence be effectively by knowing what they are showing you upon reading, knowing the scene to be captured and expecting realistically and knowing your goal that is the idea of the final image that you intend to achieve.

Once you look at the histogram, you can evaluate if you want to adjust exposure for the following image by changing certain settings or simply changing the composition of the scene to alter the amounts of dark and light spaces.

Exposure and Histograms

We have already established above that the basic aim of a histogram is to indicate the brightness of an image. Exposure basically is the effect of light on the image that is in terms of excessive light or low light.

An over-exposed image is characterized by a major body of the graph towards the right and an underexposed image by the major body towards left.

Understanding Histograms
Over Exposed Image ( Source )

A high contrast scene is characterized by a U-shaped histogram. The correct exposure is often defined as no particular concentration of the graph on either side but again correct exposure varies per perspective.

Another must read for beginners in photography is Understanding Automatic Exposure Bracketing

Understanding Histograms
Underexposed image ( Source )

The Major Use of Histograms in Photography

Histograms are majorly used in photography to tell if the exposure of a photograph is correct. While most of us as amateur photographers rely on the image we see on the viewing screen, it isn’t the correct view as what you see depends greatly on surrounding brightness and screen settings.

It is just a preview that indicates just apparent brightness that may or may not be the exact representation. A histogram, however, may be much more reliable.

Think of trying to judge a picture by looking at the screen in the glaring sun, and you will get the right idea of the reliability of histograms as compared to previews on the viewing screen. Referring to a histogram to make sure if the desired image is being achieved is the right way to approach photography.

For instance, if the goal is to photograph a dark silhouette, then higher frequencies on the left of the graph may indicate success. An evenly exposed image is similarly indicated by tones well distributed across the graph.

Understanding Histograms

Histogram data offers other reasons to adjust exposure apart from personal artistic goals related to photographs. They help one combat phenomenon of clipping that compromises detail in the picture.

Clipping is a phenomenon that causes lack of detail in a picture if the histogram touches either of the extreme edges. The condition wherein certain areas are completely white and hence detail is compromised is terme highlight clipping.

Learn about ISO in Photography

Compromise in picture quality in case that some areas are completely dark and lack detail is called shadow clipping.
These cases may be fixed by altering exposure settings, of course, depending on the scene. Such indications in histograms can help avoid these phenomena and help fix them if at all they occur.

Shadow detail can be fixed by adding positive value for exposure compensation and highlight clipping can be fixed by adding negative exposure compensation value. There are different fixes to apply but histograms indicate the need for them.

A good Histogram and Setting Exposure using Histogram

There isn’t any concept such as a good or bad histogram. They are relative terms. It is unjust to say that an image has the right histogram based on the concentration of graph in the mid areas. A histogram is an indicator that helps one take a decision about changing settings and there isn’t a good or bad about it and its perfection or rectitude depends upon your expectation from the image.

The rectitude of a histogram depends on multiple factors and hence it isn’t a perfect evaluation of exposure. It only shows the volume of tones of different brightness in the image and can be used to determine if clipping is there at a certain exposure setting. Histogram excels at avoiding loss of detail.

While some photographers may incorporate reading histograms into their photography routine, some may not find the time or incline for doing it after each shot and both of them are absolutely fine. Understanding histograms don’t make you a professional but an insight into their functioning may prove to be very useful at times.

We hope that this article made understanding histograms clear and placed you at a step closer to reading and using them.

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