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TECHNIQUE – Top 5 Tips for Quality Image Files (part 2)

 

histogram

Cloud forest vegetation, Costa Rica

KNOW YOUR HISTOGRAM

If you don’t use your histogram, you’re putting yourself at risk of underutilizing the information that your fancy DSLR camera (which truly is an amazing machine!) can capture. The histogram allows you to ensure that you’re getting as much tonal information as possible in your images, and it also allows you to focus on capturing the detail you want for certain important parts of any scene. As discussed above, the amount of information in RAW files does allow for a fair amount of post-processing without degrading the image too much. Nonetheless, getting the best exposure possible in-camera is going to mean a better final image, and you’ll also be more satisfied with your effort when you get it right.

The histogram is a big help in this regard but many people seem mystified by it. It’s actually quite simple. The histogram is basically a bar graph in which the x-axis represents the total range of tonal values in a given image from 0 to 255. That is, even in color images, there are 256 possible shades of monochromatic tonalities or luminance values, from pure black (0) to pure white (255). The y-axis indicates the number of pixels having a specific luminance value.

You’ll also see color histograms but most professional nature photographers will tell you that they don’t use these very much if at all. The only time I use them is to check the red channel in a scarlet macaw or maybe the blue in a specific flower or a hummingbird like the violet sabrewing. The consensus among the other pro nature photographers that I know, however, seems to be to master the use of the monochromatic/luminance histogram. Indeed, I have my camera set to display only this histogram by default.

histogramOne often hears that a classic bell-curve is a “good” histogram. Nothing could be further from the truth, and as an aside I think the obsession with having no bright highlights and no dark shadows has led in part to the current HDR craze (that’s a story for another post though!). That said, there are many images for which a bell-curve will indeed be a great histogram.

In the nesting toucan image above, for instance, you can see that the majority of the luminance values are clustered in the center of the x-axis. This makes sense because there are a lot of middle-toned greens
and earth tones in the image. At the tails of the graph (the left and right edges), there are many fewer pixels with extreme dark or light luminance values. And indeed, the values stop just before the left and right edges of the histogram, meaning that I have detail in the darkest and brightest parts of the image.

histogramAs this glass frog image shows, however, there is no one “good” histogram. The correct or optimum histogram will vary depending on the image. Glass frogs are nocturnal so the black background, in addition to being graphically pleasing for this image, is perfectly natural. It gives a very different histogram than the more classic toucan image above but one that is equally correct.

Note that there is a big spike of values pushed up against the left side of the histogram. This means that there are quite a lot of woefully underexposed, pure black areas. I wanted the background to be black, and so it is. You’ll also notice that there are varying luminance values represented by the dark greens and lighter greens in the image but that, importantly, there are no pixels at the right edge of the histogram. Again, this is fine for this image as there are no values that are white or even close to it. Had I put a flash on the leaves in the background in order to make the background green, the histogram would indeed have been closer to a bell-curve. That’s not what I wanted for this image though

histogramAbove is another example of a non-traditional histogram but one that is entirely correct for this image. Note here that there is a big spike that bumps up against the right edge of the histogram. This means
that there are lots of overexposed highlights; in fact, a spike this big and this close to the edge means that these values are pure white and that they contain no recoverable detail. If I had wanted this image to be a silhouette of bird and tree against a cloudy sky, I would be in big trouble because the whites are blown. Of course, that wasn’t the intention here so the overexposed whites are just fine.

 


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About the author Gregory Basco
Like many nature photographers, I started my career doing something else. A political scientist by training, my research focused on the politics of the environment in Latin America. I researched environmental politics and ecotourism in Costa Rica and worked here for a number of years as a conservation professional, having first come to the country in 1992 as a Peace Corps volunteer. I now dedicate myself full-time to my own photography and my Costa Rica photo tour company. I work out of my home office in Costa Rica’s central highlands, where I live with my wife, twin boys, our dogs and cats, and various hummingbirds and songbirds that visit our backyard feeders. Visit Greg’s galleries, store, and workshops at Deep Green Photography.

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