Show of hands: how many of you currently use the histogram to immediately adjust your shooting strategy during a session? If you’re thinking “hist-o-what,” then this is the blog post for you! It explains the basics about a histogram and answers the following questions:
- What is a histogram?
- How do I read a histogram?
- What does a correct histogram look like?
- Why should I use a histogram?
What is a histogram?
The histogram is the graph that you can view on the back of your digital SLR. It’s the graph that looks sort of like a mountain range.
Pardon me while I break into some techno-mumbo-jumbo for a moment here: a histogram shows you the brightness values of all of the pixels in your image.
I know…I know. That last sentence does not really clear things up, does it?
Let me explain it another way: imagine that you took every pixel from your digital image and organized them into piles, separating them by how dark or how light they are. All of your really dark pixels would go into one pile, your middle gray pixels would go into another pile, and your really light pixels would go into yet another pile. If you have a lot of pixels in your image that are the same color, the pile will be really big.
That graph that looks like a mountain range on the back of your camera—which we’ll now refer to as the histogram—is showing you those piles of pixels. By looking at the histogram, you can quickly determine if the shot you just took is a correct exposure. Read on to learn how.
How do I read a histogram?
If there is a big peak to the left side of the histogram—or if it is all bunched up on the left side of the grid—it means that you have a really big pile of black pixels. In other words, your image might be underexposed. If the histogram for your image looks like the following sample, you may need to increase the amount of light hitting your sensor by slowing down your shutter speed, open up your aperture, or both:
If there is a big peak to the right side of the histogram—or if it is all bunched up on the right side of the grid—it means that you have a really big pile of pure white or light pixels. You guessed it: your image might be overexposed. If the histogram for your image looks like the following sample, you may need to decrease the amount of light hitting your sensor by speeding up your shutter speed, stopping down your aperture, or both:
If your piles of pixels are fairly well spread out across the entire grid from left to right, and if they are not bunched up in any one spot, your image is a correct exposure.
What does a “correct” histogram look like?
There is no such thing as a “correct” histogram. As I said earlier, the graph shows you the brightness values of all of the pixels in your image. So while I said earlier a big pile of dark pixels might indicate an underexposed image, it doesn’t always indicate an underexposed image. Let’s look at a real-life example. Assume you took a picture of someone holding a sparkler.
The histogram for the previous image looks like this:
A lot of the pixels in this image are dark, which means that the histogram displays a peak on the left side of the histogram. A big pile of dark pixels? You bet. Underexposed? Not for the desired look of this particular image. The same limitations using a histogram might occur on a bright day, especially with a scene such as snow.
Why should I use the histogram?
Some of you might be thinking, “Why do I need to bother with the histogram? Can’t I just tell by the LCD monitor on the back of the screen if I have a correct exposure?” Well, sometimes your shooting conditions aren’t great. Bright light or dim light will make it hard to see the thumbnail view on the back. And—maybe this is just me—but have you ever looked at an image on the back of your camera and thought you nailed it, but then you upload it and it doesn’t look so hot on the big monitor?
No? That’s just me? Ok…moving on then.
Sure, you can adjust exposure in image editing software, such as Photoshop or Elements. But isn’t it better to capture the image correctly in camera? Taking a peek at the histogram of your image while you’re shooting can help you figure out if you have room to tweak the exposure of your image while you are shooting.
What about clipping and blown out highlights?
No, the following section is not about hairstyles; it is still about the histogram. Promise.
Some of you might have your camera set so the LCD blinks at you to warn you if you have completely overexposed your highlights. If you have this feature on your camera, I have absolutely no doubt that at least one time in your life you looked at the back of your camera and saw that the sky in the image that you just shot is blinking wildly at you.
Why is it doing that?!
Your camera can only successfully capture detail within a certain range of dark to light tones. This means if a part of your image has a tone that is outside of the range that your camera is able to capture, the sensor will not be able to capture detail in that part of the image. The blinking is trying to tell you, “Hey, look! The area that is blinking madly on your LCD will not have any detail in it!”
If you have ever taken a picture and the sky is blinking wildly at you, it is because that area of your image is so overexposed that the sensor has rendered it as one big blob of solid white pixels. In technical terms, this means the highlights are “clipped” or “blown.” In more realistic terms, it means that no matter what you do in your image editing software, like Photoshop, you will never ever be able to pull out detail from that section of the image.
It’s probably ok if the highlights are blown out in the sky of your family snapshot at the beach on a sunny day. Not so great, however, if the highlights are blown out and lose the detail on a bride’s wedding dress.
Instead of relying on the blinking, you can also use your histogram to quickly see if there is any clipping. If you have a big pile of light colored pixels piled high to the right side of the histogram, the detail in your highlights will be clipped, blown out, and completely lost.
What about color?
Up until now, we’ve been discussing the brightness histogram. Earlier I asked you to imagine that you took every pixel from your digital image and organized them into piles, separating them by how dark or how light they are. The piles were a combination of all the colors in your image.
Many digital cameras also provide three histograms to show you the color level for each individual RGB color channel (Red, Green, and Blue). And—just like the brightness histogram—the Red, Green, or Blue histogram shows you the individual color’s brightness level throughout the image.
Why should we care?
Let’s say you take a picture of someone who is wearing a red shirt. Imagine the red shirt is brightly lit. You look at the overall brightness histogram and it doesn’t appear to be overexposed. Then you look at the Red histogram and see a big pile of pixels piled all the way to the right side of the graph. You’ll know that the image will lose all of the texture in anything red in your image. That red shirt could end up looking like a big red blob in your image, which means that no matter what you do in Photoshop, you’re not going to be able to pull any detail from that red shirt.
Looking at your histogram will help you determine if you need to tweak your settings to keep the shirt from looking like a big red blob.
The histogram—like so many other areas of photography—allows you to determine what is correct for the type of image you are trying to capture. The next time you’re taking a shot, take a look at the histogram of your image to see if you have room to make any adjustments to your settings while you’re shooting. Histograms are also useful in post processing when using various adjustment layers.
Maggie is a recovering technical writer who is the photographer behind Maggie Wendel Photography. Based in Wake Forest, NC, Maggie specializes in portraits of newborns, babies, and children.Announcement: Winner of the iPad2
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