Understanding the histogram
Video: Understanding the histogramiPhoto offers a useful tool, so you can measure the exposure in your image. Remember, exposure is how much light is coming into the camera, in many ways, and this will show you the dark and the bright areas of an image. Being able to read the histogram, that particular scope, is very useful. With the picture open, if I go into Edit mode, and click Adjust, you'll see that we have a histogram here. In this particular case, it's showing that on the left are the shadowy areas, and on the right are the bright areas.
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Almost every photo can benefit from some enhancement, from exposure adjustments to cropping. In this course, author Rich Harrington shows how to improve photos using iPhoto. The course describes how to crop and straighten photos; remove red eye; improve exposure, color, and contrast; and refine images by retouching blemishes, removing noise, and adding special effects like vignettes.
This course was created and produced by Rich Harrington. lynda.com is honored to host this content in our library.
- Cropping for better composition
- Rotating an image
- Making a levels adjustment
- Adjusting shadows or highlights
- Increasing saturation
- Converting to black and white
- Creating sepia-tone effects
- Using the Retouch Brush
- Sharpening photos
- Adding borders
- Copying and pasting adjustments
Understanding the histogram
iPhoto offers a useful tool, so you can measure the exposure in your image. Remember, exposure is how much light is coming into the camera, in many ways, and this will show you the dark and the bright areas of an image. Being able to read the histogram, that particular scope, is very useful. With the picture open, if I go into Edit mode, and click Adjust, you'll see that we have a histogram here. In this particular case, it's showing that on the left are the shadowy areas, and on the right are the bright areas.
You're also seeing individual components of color being represented: the red, green, and blue. With light, we use the RGB color space. Essentially speaking, if you remember back to high school science class, or maybe even preschool, for that matter, when you split white light, it becomes a rainbow; ROYGBIV. Well, red, green, blue is the easy way that computers use to split light, and when we make pixels, and we combine them, using red, green, and blue pixels, we get different colors to make a digital image.
That's what you're seeing here; a high value of green and red down here in the shadowy areas, which makes sense, because we have this reddish dirt, and this greenish vegetation. Now, over here, the brightest areas, which is this spike here, is the blue sky, and we're definitely seeing that, and this is helping you understand how the images are reading. If I switch to another photo, notice that there is a spike here, sort of in the middle.
This particular image is fairly flat. It's a little bit bright, but all the details are being pushed into this lower end. Later on, as we start to make adjustments, what you'll see is that we'll work to balance out that information, and try to find proper exposure. This image is a bit tough, however, because there's not a lot of information to work with, and we're going to have to do some trickery to resolve it. Even still, just that quick adjustment definitely helped with the contrast.
If we look at this image, we see that it's a bit overexposed. Notice all the details here smashing to the right of the histogram. This is telling us that we have overexposed areas, and you see that large spike right here. Fortunately, this is a RAW file, meaning that there's extra information. So I could pull the exposure down, and recover a wide range of details. Notice that what used to be blown out in the sky actually can come back.
And then, using the Shadows slider, I could recover those skintone areas. Put a little Definition, and a little Saturation in, and all of a sudden, we're starting to get a better image. Here we go. Now, that's a bit underexposed, but if you look at the before, and the after, you see how the histogram changes to represent what's been done in the image itself. You'll see a lot more about the histogram as we work with images, particularly exposure.
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