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Arriving at the best exposure for a photo is part science and part art. In Foundations of Photography: Exposure, Ben Long helps photographers expand their artistic options by giving them a deep understanding of shutter speed, aperture, ISO, and all other critical exposure practices. This course covers the basic exposure controls provided by all digital SLR cameras, as well as most advanced point-and-shoot models. Learn how to master a camera's metering modes, how to use exposure compensation and bracketing, and much more. By the end of the course, you'll know how to develop an "exposure strategy" that will allow you to effectively employ your exposure knowledge in any shooting situation.
Earlier we looked at a live histogram display from a camera. That's where I see a histogram superimposed over my scene on my LCD screen on the back of my camera. A live histogram can be useful. The problem with it is, as you move the camera around, the histogram is jumping all around. I find it pretty complicated. I prefer to work by shooting an image and then reviewing the image and turning on a histogram display on the back of my camera. Here is a kind of a typical information view in playback mode on a camera, and as you can see, I have got a histogram here.
If you go into playback mode on your camera, and you don't see a histogram, you will just see a big full-screen image, maybe with some of this exposure data or not, it doesn't mean your camera can't generate a histogram. It may just mean that you have to cycle through a couple of different screens of information before you get to something like this. And here you can see exactly what we saw before. This is a typical histogram. I have got black over here, white over here, and so what I am seeing from this image is that I don't have any real strong black in this image. I don't have any actual white. The bulk of my tones are down here below middle gray.
So, this is kind of a typical histogram view that you would see in a camera. What I want to do now though is look at some real-world examples of just some more histograms, just because you kind of need practice learning to read a histogram. Here, I have got an image, a grayscale image, and you can see again, this is a histogram generated by Photoshop. So it doesn't really matter who is generating the histogram. It's still just a bar chart of the distribution of tones in my image, with black on the left, white on the right. So, I am lacking the full black here, and that's why the image maybe lacks a little bit of punch, these dark shadows over here that should be complete black or not.
I have got a little tiny bit of overexposure. That's what this spike is over here on the right side, and that's probably coming from these white bits in here. I have got a lot of gray, dark gray. That's probably going to be the baby flamingo and just the dirt here. These darker tones are going to be all these shadows and things back here. Here is a color image. This image is underexposed, and I can tell because there is a big black spike on the left side. Now, I can also tell because there is a whole bunch of black over here that lost all detail back here. In this case, I don't mind.
Loosing shadow detail is not always a bad thing. But again, what's nice about having the histogram is that I can tell this on the back of my camera. No matter what the image looks like, the histogram tells me I have lost detail in my shadows; overall the image is pretty dark. I don't have any really bright white stuff. Here is the opposite problem, an image that's overexposed. I have got a spike over here. Actually, I have also got a little bit of underexposure. So, these white bits, I had lost some detail on the fur here, the black bits, I have lost some detail in here. But I have got a good amount of data overall.
So far, none of these histograms are necessarily incorrect. This image, for example, is for the most part, I would consider this well exposed. Yes, I don't have a whole bunch of white over here, but there is nothing really bright white in the image. If I expose it too much more, I am going to lose detail on this part of her skirt. So, again, there is no correct shape; you want a histogram that corresponds well to the actual tones in your image. Right now, we are just practicing reading the histogram. This image is low contrast. Now, you can tell that by looking at the image. It looks pretty dull and flat, and that's because it was shot on kind of a hazy day, in the middle of the day.
But when I look at this on the back of my camera, it might be punched up a little bit. So fortunately, I have a histogram that shows me there is essentially no black, no white, and for the most part all the tones are gathered in the middle of the histogram. There is not a lot of distance between the darkest significant tone and the lightest significant tone, meaning there is not a lot of contrast between these two points. This was a case where I shot the image, and because I knew that it was a potentially low-contrast scene, I looked at the histogram, saw that there wasn't a lot of data here, so I increased my exposure using exposure compensation.
I went up about 2/3rds of a stop, and look: I have picked up a lot more detail. There is still no dark black, there is no white, but I have got a nice range, a bigger range from the darkest to the lightest tones. What this means is I have more data to play with when I get into my image editor. I am going to be able to push these dark tones further down, lift the light tones up a little bit, and get an image that's more contrasty. Here is an image that appears to lack a lot of midtone data. It's got a whole bunch of shadows, and it's got a bright highlight over here. But this histogram is pretty good for this image, because this image doesn't have a lot of mid-tone data; it's mostly some really dark shadows, a bunch of bright highlights.
So you don't necessarily always look for that histogram that's the perfect distribution from a little bit of black into some nice white with every shade of gray in between; the histogram has to represent what's in your image. If you are shooting a penguin on a black-and-white checked tablecloth, you are going to have a bunch of dark tones and a bunch of light tones and not much in between. That's kind of what we have got here. So this histogram is correct for what's in our image. You camera might display a histogram that looks something like this. Now, I am looking at two different shots of an image here. I am seeing four different histograms.
This is the overall composite histogram, like we have been looking at, but it's also giving me a separate histogram for the red, green and blue Channels, for the red, green and blue information in the image. And what this can be useful for is detecting when you have possibly got a bad white balance. And here is one where you can see that I was shooting with tungsten white balance, even though I was outside at night. And here notice that the histograms are all kind of in the same place. They are kind of registered. This hump is all on the same spot on each histogram, and that means that my red, green, and blue are combining properly to make true white.
Here, I have got more blue in these upper tones, and that's giving my image more of a color cast. So, your histogram can also be useful for predicting and determining if you have got a color cast in your image. The histogram will make more sense as you practice, particularly once you get into your image editor. That's an essential tool at both, when you are shooting and when you are editing.
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