The Histogram
The histogram is one of photographers' most powerful yet frequently misunderstood tools. It’s a graphical representation of the brightness levels in an image. In more technical terms, it shows how many pixels in an image fall into each brightness level, ranging from pure black on the left to pure white on the right. It can dramatically improve your photography by helping you achieve optimal exposures and understand the distribution of light in your images. Wherever you are on your photographic journey, mastering the histogram will elevate your skills.
A Little Bit of History
The histogram in photography has deeper historical roots than many realise. In about 1939, Ansel Adams and Fred Archer formulated a technique for determining optimal film exposure and development called the "Zone System". This system was crucial during the film era when photographers had no immediate feedback on their exposures.
Adams believed that the "perfect" print contained eleven zones of tonality ranging from pure black to white. The Zone System categorised tones as follows:
Zone 0: Pure black
Zone I: Near black, with slight tonality but no texture
Zone II: Textured black; the darkest part with slight detail
Zone III: Average dark materials showing adequate texture
Zone IV: Average dark foliage, dark stone, landscape shadows
Zone V: Middle grey (18% grey card); clear north sky
Zone VI: Average Caucasian skin; light stone
Zone VII: Very light skin; shadows in snow with side lighting
Zone VIII: Lightest tone with texture (textured snow)
Zone IX: Slight tone without texture
Zone X: Pure white
This systematic approach to tonal range was revolutionary and laid the groundwork for what would later evolve into the digital histogram. During film photography, this was a crucial tool in achieving the correct exposure, ensuring that highlights were not blown out and shadows retained detail.
What Exactly Is a Histogram?
The dictionary definition of a histogram is more than a little confusing, but essentially, it’s a graphical representation of the pixels exposed in your image, rating their tonal value from pure black to pure white, where black = 0 and white = 255. A higher concentration of data on the left-hand side of the histogram represents a larger number of pixels with a dark tonal value—for example, deep shadows in a dimly lit room—whilst a high concentration to the right means your image is awash with light tones, such as bright sunshine on a white wall. The middle of the graph represents mid-tones, exemplified by the 18% grey card reading.
The horizontal axis represents the range of tones from 0% brightness (black) on the left to 100% brightness (white) on the right. The vertical axis represents the number of pixels at that particular brightness level. The higher the graph at any point, the greater the number of pixels with that tone—or, to put it another way, the larger the area of that tone in the image.
Histograms are available on most phones and digital cameras and in editing software such as Snapseed, Lightroom, and Photoshop. They provide an objective mathematical representation of your image's exposure that your eyes alone cannot reliably determine, especially when viewing images on inconsistent camera LCD screens.
In Snapseed, the histogram appears as a graph icon in the lower left corner of your screen. Simply tap this icon to display the histogram, or tap it again to minimise it. The histogram will remain visible while using the Tune Image tool as a helpful exposure guide during editing.
Types of Histograms
When working with histograms, you'll encounter two main types:
Luminance Histogram: The luminance (or brightness) histogram displays the brightness levels from black to white without distinguishing between colours. This is the most common type of histogram, which most photographers refer to when discussing "the histogram". It's beneficial for assessing overall exposure.
RGB Channel Histograms: RGB histograms show the range of tones for each of the three colour channels—red, Green, and Blue. They allow you to see if any colour channel is clipped or underexposed.
In a colour channel histogram, the more the graph rises to the right-hand side, the more saturated that colour will be in the image. Conversely, if the graph rises to the histogram's left, the colour is more muted in the image. RGB histograms are invaluable when shooting colourful subjects where one channel might clip even if the overall exposure looks balanced.
Reading and Interpreting the Histogram
The histogram can be understood as a left-to-right graph representing the tonal range of your image. The left edge of the graph displays shadows, with the furthest left point indicating pure black (0 on the scale). The right edge represents highlights, with the furthest right point showing pure white (255 on the scale). The middle section of the histogram represents all the mid-tones or middle greys in your image. Higher peaks or "spikes" in certain areas indicate that your image contains more pixels of that particular tone.
Understanding how to read a histogram is essential for improving your photography. Here's a breakdown of what different parts of the histogram represent:
Left Side (Shadows): The left side of the histogram represents the dark tones or shadows in your image. If the histogram shows high peaks on the left edge that appear to be cut off, this indicates shadow clipping or crushed shadows – where details in the darkest areas are lost.
Middle Portion (Midtones): The central part of the histogram represents midtones, areas that are neither incredibly dark nor bright. These midtones often make up the majority of images.
Right Side (Highlights): The right side represents bright tones or highlights. If the histogram shows peaks running off the right edge, this indicates highlight clipping or blown highlights, where details in the brightest areas are lost. In digital photography, recovering blown highlights is often more difficult than recovering shadow detail, making highlight clipping particularly problematic.
When editing, pay close attention to how adjustments to brightness, contrast, and other settings affect the histogram's shape and position. For example, in a primarily dark image, you will see a prominent peak with most pixels bunched up toward the left (darker) end of the graph. The opposite is true, with a mostly bright image having its pixels bunched up at the right (lighter) end of the histogram curve. This shape will change as you adjust the parameters in the Tune Image or Curves tools.
Common Histogram Shapes and What They Mean
The shape of your histogram provides valuable information about your image:
Well-Distributed Histogram: A histogram that spans most or all of the tonal range without significant clipping on either end typically indicates a well-exposed image with a good tonal range. However, it's important to note that there is no single "correct" histogram shape – the ideal distribution depends entirely on your subject and creative intent.
Left-Skewed Histogram: If your histogram is bunched up towards the left side, it indicates an underexposed image, or you may be photographing a naturally dark, low-key scene. When this is unintentional, you can let in more light by lowering the shutter speed, widening the aperture, or raising the ISO.
Right-Skewed Histogram: If your histogram is bunched up towards the right, this suggests an overexposed image, or you may be photographing a naturally bright, high-key scene. When this is unintentional, you can reduce the light by using a faster shutter speed, narrowing the aperture, or lowering the ISO.
Narrow, Centrally Bunched Histogram: If all your tones are packed into the middle area of your histogram with space on both sides, your image likely has low contrast. This can be addressed by adding light to intensify highlights and deepen shadows or by adjusting contrast in post-processing.
Bimodal or Multimodal Histogram: A histogram with two or more distinct peaks indicates a scene with significant contrast between elements. This is common in high-contrast scenes like sunsets or scenes with strong backlighting.
What Makes an Ideal Histogram?
Whilst no single histogram shape works for all images, an ideal histogram typically displays a balanced distribution of tones stretching across the graph without being heavily skewed to extremes. For most well-exposed images, the distribution should reach from end to end, ensuring a pure black point, a pure white point, and a good range of tones in between.
A well-distributed histogram might hump evenly in the middle and only just reach both sides, signifying a large spread of even midtones, some black and some white, but the reality is different photographic subjects will be represented differently. While some subjects are biased towards light or dark tones, many complex scenes require a more even spread. Trying to ascertain a correct exposure by squinting at an image on your camera’s tiny LCD screen might not inspire confidence, but a histogram can instantly tell you if you can dial an exposure up or down without compromising your overall shot.
However, be cautious of clipping–when the histogram touches the far left or right edges. This indicates areas where detail has been lost to pure black or white–also known as blown highlights and crushed shadows. If your histogram shows significant clipping and you wish to preserve detail, adjust your brightness, shadows, or highlights in the Tune Image tool until the shape shifts away from the edges.
If your histogram has gaps at either end, you are missing pixel data for dark or light tones. You can shift your exposure to cover a better tonal range.
If the histogram lacks data in the whites, you can dial up your exposure and reshoot to represent the scene better and shift the spread to the right.
If your scene has significant gaps to the left, you may want to reduce your exposure to find true blacks and detail in the highlights.
If an image results in spiking at either end of the histogram, this is known as clipping. A spike out the top of the histogram suggests you may not be able to recover the pixel data for those tones, whether they are highlights or shadows. You may want to address this with your exposure, or it may be an aesthetic choice you’ve made.
Some scenes may contain too much dynamic range for the camera to capture both highlight and shadow detail. Think of a shadowy, dimly lit room interior, with a window showing a brightly lit exterior. You won’t be able to expose these two key areas of the scene perfectly with one shot, and your histogram will likely show spikes at both ends and, quite possibly, clipping. This doesn’t make it incorrect; it’s just a challenging scene for the sensor to interpret. Like many things in photography, there are numerous workarounds to attaining great results in such situations.
So, whilst some exposures might be deemed “wrong” for a particular scene or brief, others will be artistic choices made by you as the photographer. Whilst histograms can be a handy tool, do not slavishly adhere to them to the detriment of your creative vision.
Using the Histogram to Improve Your Edits
The histogram in Snapseed can help you set proper white and black points for your image, and it is an essential tool for ensuring your image isn't severely over- or underexposed.
When editing, if you notice your histogram bunched up against the left side, your image is likely too dark and could benefit from increased brightness or shadow adjustments.
Conversely, if it's pressed against the right side, your photo may be overexposed and require reduced brightness or highlight adjustments.
By learning to "read" your histogram, you'll develop a more technical understanding of your images' exposure, resulting in more balanced and visually appealing photographs.
Practical Applications of Histograms
Histograms offer numerous practical benefits for photographers:
Exposure Evaluation: The primary use of histograms is to evaluate whether your image is correctly exposed. Unlike the camera's LCD screen, which can be affected by ambient light and brightness settings, the histogram objectively represents your exposure.
Avoiding Clipping: Histograms help you identify and prevent clipping – the loss of detail in extremely dark or bright areas. By monitoring the edges of your histogram, you can adjust your exposure to preserve detail throughout the tonal range.
Assessing Contrast: The width of the histogram indicates the level of contrast in your image. A narrow histogram suggests low contrast, while a wider histogram indicates higher contrast.
Shooting in Challenging Conditions: Histograms are particularly valuable when shooting in bright sunlight where the LCD screen is difficult to see clearly. They provide a reliable method to check exposure regardless of viewing conditions.
Real-Time Feedback: Many smartphones and modern cameras offer live histogram displays, allowing you to see how changes to your settings affect the exposure before taking the shot. This feature is invaluable for learning how different settings impact your images.
Best Practices for Working with Histograms
To get the most from histograms in your photography:
Shoot in RAW Format: RAW files retain all the data captured by your camera, giving you maximum flexibility to adjust exposure based on histogram information during post-processing.
Expose to the Right (ETTR): Many photographers deliberately "expose to the right," pushing the histogram as far to the right as possible without clipping highlights. This technique captures more data in the brighter areas (where digital sensors excel) and can result in cleaner images with less noise when properly processed.
Use Histograms Alongside Your Creative Vision: Remember that histograms are tools, not rules. Sometimes a "technically incorrect" exposure creates the mood or effect you want. Use histograms to inform your decisions, but let your creative vision guide the final result.
Check Individual Colour Channels: For colourful subjects, check the RGB histograms to ensure no single colour channel is clipping, even if the luminance histogram looks acceptable.
Resources
Here’s a very clear video summary from Paul Farris at Photo Genius, where he shows some excellent photographs as examples and explains how to interpret their histograms.
And this video, from the inimitable Henry Turner, takes us out on location shooting waterfalls in the Lake District, and demonstrates step by step how the histogram makes getting the correct exposure simple.
Give it a Try!
The histogram is far more than just a technical graph—it's a powerful tool that can transform your understanding of light and exposure in photography. By mastering how to read and interpret histograms, you can gain valuable insights into your images that the naked eye may miss.
From its historical origins in Ansel Adams' Zone System to its modern implementation in digital cameras and editing software, the histogram has evolved into an essential component of the photographic process. Whether you're capturing dramatic landscapes, delicate portraits, or challenging high-contrast scenes, the histogram provides objective feedback to help you achieve your creative vision.
By incorporating histogram analysis into your photographic workflow, you'll gain greater control over your exposures, reduce post-processing corrections, and ultimately produce images of higher technical quality that better express your artistic intent.
