Last Updated on 06/19/2011 by Chris Gampat
In these days of the digital SLR, we’ve all seen these weird graphs, jagged and erratic like the output from some radioactive geological experiment. Most modern cameras allow quick access to these cryptic readouts. They come in a range of sizes and colors, instant review, live feedback, even histograms for every color channel. So are they useful? Can they help us to take better photos? In this quick 3-part series, we’ll dive into the power of the histogram and, hopefully, share a few handy tips.
What the Hey is The Histogram?
The histogram is a graph representing all the tones a camera is capable of capturing, from pure black on the left to pure white on the right. If we were discussing piano music, a histogram would be a bar graph with one bar for each key on the keyboard, as tall as the number of times the key is pressed.
And it’s not totally random, by the way, to discus histograms and pianos in the same sentence.
Photography great, Ansel Adams, was also a pianist and often described his photographic work in keyboard terms. He advocated using all 88 keys in a photo, from black to white and everywhere in between. Blacks should be dark and substantial, but with good detail and transitions, like the last few octaves on the keys, not just the wobbly final “A” at the end. Highlights, also, need to be contained within the reach of the instrument, and not tinkered away in the wimpy last notes to the right.
How can a digital histogram help in this most musical of efforts? On your camera’s LCD screen you can actually get a quick glimpse at which “keys” are getting the most action and quickly see how what you see in front of you has been recorded by the camera.
Take this wedding cake for example. It’s white, not perfectly, flatly, staring-in-the-sun white, but certainly a very light color. It has a couple light blue ribbons and a wad of lightly-colored flowers on top. Besides the light colors, there is a rather medium-dark, mixed-color background and a few dark details: like flowers, stems, and shadows. So—on the digital piano—we’d expect to see a lot of activity in the high end, not the highest end, but close. We’d also expect a lesser flurry of notes in the middle-low end of the spectrum.
In the first histogram, you can see a good-size hill in the right third of the graph with a number of impressive spikes. There are spikes that coordinate with the light blue ribbons, the light-light green flower details and stems, and light-light-light cake color, which appears to contain lots of red, a good deal of green, and some yellow. To the left, there are mounds corresponding the dark background and various foreground details.
So Which One is Best?
For an image like this, the first histogram represents good news for the photographer. Both the whole cake and dark background are captured in nicely filled-out humps that speak to good detail in every part of the image. Once the exposure begins to blow out, that is to say over-expose, the highlights “ramp” off the graph, as if building towards a peak that happens off-stage. In the second image and corresponding second histogram, you can see that the image is too bright and that the histogram looks like a ski jump: not good! Notice the colors are no longer nicely-defined and the lack of low-end bump. If this were a piano piece, we’d be saying, “Turn up the bass!”
The third image and histogram show an underexposed version of the image. Notice the right-hand high-end is gone and that many of the tones are jammed up in the muddy region on the far left. Visually, that translates to dark, uncertain areas in the image. The metal “P” and flowers get lost in the darkness and hardly any detail is visible in the background.
Of course, ski jumps and muddy left-hands can be important tools of expression in certain circumstances, as we’ll discuss in Part 2. Sometimes, after all, a photographer wants dark, uncertain areas in an image (perhaps less frequently in wedding photography). For now, though, it’s pretty cool to have a dependable and objective way to check exposure. In certain lighting, it’s hard to tell from a camera LCD alone, and cameras tend to vary from screen to screen. It’s all in the histogram, though.
To conclude, here’s a quick histogram checklist to run through when judging a capture:
1. Did the Highlights Blow?
Avoid the ski jump. You can tell in a glance if there are areas that are gone to white. Sometimes, it’s hard to avoid. Perhaps reframing to not show so much sky (a frequent culprit of the ski jump) or just lowering the overall exposure with Aperture, Shutter Speed, or ISO can help.
2. Is There Good Detail in The Shadow Areas?
Are there dark areas that are too muddy to look good? Try upping the exposure to keep detail. As you can see in the dark #3 wedding cake above, the muddy histogram makes for an ugly shot! (although, it does help my white watermark to stand out nicely!)
3. Are All 88 Keys Getting at Least a Little Action?
This is important. If you have empty space at either end of the histogram, you’ve probably got a flat-looking image. Notice that both the too-bright and too-dark cakes have under-utilized piano keys in their histograms. A nicely spread curve with good detail at both ends translates to good visual contrast.
This is a great histogram (how often do you hear a photographer say that?) Neither the highlights nor shadows have blown (everything is contained in the graph with no ski jumps) and there is good data from end to end (indicating a lively experience for every note on the keyboard). Though the image contains areas that are bright and areas that are dark, good detail is maintained throughout and contrast is likely to be quite nice.
Plus it’s a cute shot, right?
In Part 2, we’ll dive into those exciting situations when it’s good to get muddy or build a nice big ramp. In Part 3, we’ll look at post processing with the histogram. In the meantime, you might enjoy exploring the quick info available from your camera’s histogram!
All histograms in this entry were taken from Adobe Photoshop Lightroom 3.3
Questions? Ask away in the comments below.
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