When using a traditional film camera, to properly expose your shot you had to rely on an analog light meter needle. Before the advent of the digital camera, the light meter (whether in-camera or as an external tool) was the only means of gauging proper exposure (other than memorizing reciprocity tables). Modern digital cameras have this, too, and in multiple places:
There is a more detailed way to see if your scene is properly exposed though. While the built-in meter is fantastic for quickly telling you whether you’re over or under exposed, it is not great at telling you about highlights and shadows. This is where the histogram comes in!
What is A Histogram?
A histogram is a bar graph showing the frequency distribution of values in a set of data. It appears as a smooth curve since there are often a high number of data points (bars) on the graph. A lot of us might think of histograms as only a photography thing, but histograms are used in all kinds of research. Histograms are just bar graphs except each “bar” represents a range of values (or intervals, referred to as “bins”) and not just 1 point of data. In photography, there are luminosity histograms and color histograms. Luminosity histograms show the distribution of brightness level of pixels overall, while color histograms show this distribution for red pixels, blue pixels, or green pixels.
Types of Histograms in Photography
When photographers hear “histogram” they are actually hearing about one of the sub-sets of histograms: luminosity histograms and color histograms. But a lot of folks just say “histogram” for short.
Luminosity histograms (also called “image histograms”) plot a range of pixels (“bins”) for reach tonal value. This is useful to us because we can then get an idea of the tonal distribution of our image at a glance. In other words, the histogram tells us whether any part of our image is way over-exposed (blown-out) or under-exposed (blacked-out). Fully blown or blacked areas of an image can’t be recovered in post processing – even if you shot in Raw. It’s important to cross-check your histogram with your light meter because your metering may still say your scene is overall “exposed” while still having parts of the scene blown-out/blacked-out.
In a luminosity histogram, the bottom horizontal axis of the graph depicts the bins of pixel brightness, from dark (left) to bright (right). The vertical axis shows the frequency (amount) of image pixels in each brightness bin, where higher traces of the graph’s curve are more pixels, and lower are less. If you find it hard to remember which side of the graph represents dark vs light, think about black and white photography: we always refer to it as “black and white” photography and not “white and black” photography. When written, that reads left to right – same direction as on the histogram.
Below is an example of three luminosity histograms, a dark image (left), a normal image (center), and a bright image (right). The shape and position of the luminosity histogram’s curve provides info on the brightness or darkness of the photo – if the curve is bunched up to the left, the image is likely darker than it is light; if the curve is bunched to the right, the image is brighter than it is dark.
What this means in terms of what’s going on with exposure is that a dark image (more area of the image is dark than bright) will have more taller stacks of pixels creating a higher curve on the left side of the histogram, while a bright image will have more stacks (and thus the bulk of the histogram’s curve) to the right. An evenly exposed image, with equal parts dark and equal parts light, will have a “bell curve” shaped histogram, with the majority of the data in the middle of the range of dark to bright.
Color histograms (also called “RGB histograms”) show the distribution of brightness level (frequency) of red pixels, blue pixels, or green pixels. Here’s an example from Canon:
If an individual channel’s curve is bunched up to the left side of the RGB histogram, that color is darker and less prominent in the image (i.e. information on that color is lacking). If the curve is pushed to the right, the color is denser and brighter (there is ample or even too much information on that color – it is over-saturated and doesn’t possess a smooth gradation). Color histograms are more often paid attention to in post-processing vs luminosity histograms which are a vital tool when shooting.
Where to Find and View Histograms on Your Camera
Each manufacturer is different, but most modern DSLRs and mirrorless systems will show the histogram both in Live View before taking a photo and during Image Review (playback). With Canon, you can review the histogram live as you shoot by entering Live View mode (Start/Stop button on the 5D Mark IV), then you cycle through the Info button until it is displayed on the center right of the image. This works best if “Exposure Simulation” is turned on in the shooting menu.
When used with Live View and Exposure Simulation, the luminosity histogram provides an instant, powerful tool to quickly adjust exposure by adjusting any of your three variables (shutter speed, aperture, or ISO), which “pushes” the histogram to the right (brighter) or “pulls” it to the left (darker). You can also “play” (Image Review) an image you already took and then cycle through the Info button to check both the Luminosity and the RGB histogram.
Here are three separate photos of the same scene, bracketed down in exposure, with the luminosity histogram shown beside the image as it is reviewed on the LCD screen of a Canon 5D Mark IV camera:
How to Read a Histogram
The real power of the histogram comes when you monitor it as you shoot. The astute photographer knows that post-processing, whether done via Adobe’s Camera Raw (Lightroom/Photoshop/Standalone CR) or the native camera processors (Nikon Studio/Canon Digital Photo Professional), is done with algorithms (math equations) on the data collected by your camera’s sensor. In theses digital darkrooms, moving developer sliders around or using equations to brighten or darken an image either won’t work or will yield undesirable results if there isn’t any information there to begin with. These extremes are noticeable not when the histogram is merely bunched up to one side or the other, but when it is climbing the wall! If the graph has rocketed up one side, you’re going to have trouble with the file later on.
Thus, the luminosity histogram is what to watch while shooting, particularly while shooting outdoors. If the histogram has a portion of data “climbing the wall” on the left side, the image is underexposed and has areas that are pure shadow (RGB 0,0,0 with zero shadow detail). No amount of post-processing will add usable information in these areas.
Conversely, if the histogram has areas that are climbing the wall to the right, then the image has pure white areas or is overexposed, with RGB Values of 255, 255, 255. This may be on purpose if the image has areas of clouds or snow that by their nature are pure white and lack a lot of highlight detail. But again, no amount of post-processing will bring out any useful information here.
There are scenarios in landscape photography where you may desire pure black or pure white. For example, if you shoot with the intention to create black and white images that mimic the Zone system pioneered by Ansel Adams (where you aim to have all tonality levels from pure black through pure white). Perhaps you shoot commercial photos with people or objects where extreme color saturation is important. If so, you will want to carefully monitor your RGB channel histograms because the individual color channels need to have the right amount of gradation and/or saturation to deliver color-correct work to your clients.
Expose to the Right
There’s a philosophy in modern digital landscape photography called “Expose to the Right” or ETTR. Developed in 2003 by photographer Michaell Reichmann and Thomas Knoll (Photoshop developer and creator of the Camera Raw plug-in), ETTR prescribes adjusting digital Raw image exposures “to the right” (brighter) by adjusting shutter speed or ISO to the point the luminosity histogram just begins to clip (climb the wall). To visualize reaching this point, you make combined use of the luminosity histogram and your camera’s “highlight alert” feature, which is where areas of the image at this critical point of exposure level will start to blink.
In Canons, this can be found in the “Play” menu, Screen #3 (set to “Enable”).
You can still bring back detail in these areas if a small portion of the images “blink” as overexposed because histograms are constructed from a temporary JPEG preview of the Raw image to cut down on processing power needed in a camera’s electronics hardware; in the Raw file there is still usable information in these areas even though the highlight alert says there is not.
To avoid this, seek the perfect exposure. If you believe in the ETTR philosophy, the perfect exposure is when you see ~1-5% of your image blinking with a highlight alert and there is a very small, or no, part of the histogram climbing the left side of the graph (no pure shadows). This is how I set myself up for success in post processing with Camera Raw in Lightroom.
Here is an example of the four Bristlecone photos with “blinkies” on/off and their accompanying histograms viewed during image review on the back of the camera. These four frames were shot from brighter to darker:
Take a look at a bracketed set of Raw landscape images, shot in the Ancient Bristlecone Forest in California’s White Mountains (you can download these images here from Dropbox). In this late afternoon lighting, the total dynamic range from the bright areas of the clouds through to the dark areas of the tree was too great for my camera’s sensor – I could not set the exposure to capture adequate information in one single frame. So, with Live View on and Highlight Alert enabled, I monitored my histogram and bracketed 4 separate photos to capture the total dynamic range of the scene.
Lightroom shows the luminosity and RGB histograms laid atop one another in the Develop module. The luminosity histogram is in the front and is white and the RGB histograms are behind the luminosity histogram. Lightroom has another useful feature that identifies pure black pixels in Blue and pure white pixels in Red if you click the triangles at the upper corners of the histogram.
At the other end of the luminosity scale, here is another image showing areas of pure shadow:
If you only want to see the luminosity histogram in Lightroom, simply temporarily desaturate the color to -100.
To create the finished version of this image, I used the “Merge to HDR in Photoshop” feature and generated a 32-bit DNG file built from a combination of the four images, with the complete and full dynamic range:
Keep an eye on your histograms as you work on an image in Lightroom, particularly as you adjust the shadows and highlights sliders, and the white/black sliders. Each slider adjusts the exposure values in the corresponding part of the histogram, which you can see by moving your mouse over the histogram itself. The “ISO 100 | 20mm | f/13 | 1/60th” information will disappear and be replaced by “Blacks | Shadows | Exposure | Highlights | Whites” and clicking and dragging on the histogram will cause the corresponding slider value to change.
With Black and White Conversions, you can also view the histogram of the color image and adjust the sliders to increase the contrast if you have an image lacking in contrast in the lighting conditions when you captured it. There is room to increase the exposure to the right to ensure that the water goes to pure white in the conversion.
I frequently leave the shadow alert on in Lightroom’s histogram when working night images and use this as a guide to how far I can add light into the shadow areas before noise becomes too high and renders the image unusable; I also deliberately process areas of the sky between stars to be pure black.
Histograms are a powerful tool in digital photography. If you learn to monitor them while shooting and editing photos, the feedback they provide leads you to not only the perfect exposure but also helps you produce more interesting landscapes.Tags: Best Camera Settings, metering Last modified: June 2, 2020