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Let's discuss bit depth, and get that little bit of technical nuance out of the way. I know you're thinking, ah! Why do we have to do bit depth, all that technical stuff? Well, as it turns out most of your good scanning interfaces actually include bit depth as part of the description and the choices you have when you're selecting scan mode. So rather than just kind of wonder about what it is let's go ahead and dig in just a little bit, understand what bit depth is and then it becomes an actual proactive choice that you can make. The good news is there are only three fundamental image bit depths that we work with.
1 bit black and white, 8-bit grayscale, and 24-bit color. All the other bit depths that we will deal with are really variations on those three fundamental image types. So let's just dive right in. Let's start with the simplest of all kinds of images and this is the 1-bit black and white. I am going to enlarge this and notice that down when it's smaller it almost looks like a continuous tone grayscale image like the middle one, but there is a little bit of graininess to it. And when we enlarged this we see why there's graininess, because this image is actually constructed out of nothing but black and white pixels.
To help us understand this whole concept of bit depth and the real issue is the relationship of bit depth to shades of gray. We are going to enlarge and we are going to use our Channels panel and our Info panel. Let's take it up even one more. there we go, get a good view of those pixels. Notice that this image is constructed out of nothing, but black and white pixels. It's a diffuse pattern of black and white pixels to create something that looks like a continuous tone image if you look at it just the right size, but this is the simplest of all images as I mentioned, because there is only black pixels and white pixels.
To understand the relationship between these black and white pixels, let's use our Info panel to look at the K value and the RGB value. Just a little bit of review remember K value goes from 0-100% and the RGB value goes from 0-255, where 0 is pure black and 255 is pure white. Honestly, when we are working in most scanning programs there are typically 0-255 values that you're working with, so it's good to get a handle on that and used to working in those. We call these digital images for reason, because anything that's digital either a device or an image or a software program is digital because it only works in two numbers 0 and 1 and those are called bits, the basic bits, there is a basic digital alphabet if you will.
There are only two characters in our digital alphabet, 0 and 1. Luckily, there's a match in this simplest of all images. How many shades of gray do we have here, only 2, pure black and pure white. This is indeed a grayscale image. It's just a simple one. it's a bitonal image with black and white. In order to construct this image all we need to do is assign one of our two bit values either 0 or 1 to each pixel. So say 0 to the black pixels and 1 to the white pixels, and that's how we construct this image 0, 1, 1, 0, 1, 0, 1, 1, 0 and so forth.
We assign one bit of information either 0 or 1 to each pixel and that's how we construct the image and that's why we call this a 1-bit black and white image, because we have two shades of gray, black and white it only takes one bit of information. Notice in Photoshop channels we see there is only one channel. We only need one channel to construct this image and only two shades of gray and two bits of information, one assigned each pixel to construct this image. Notice that Photoshop uses the word bitmap when it's using this 1-bit black and white channel.
So that's the fundamental background of all shades of gray and all tonality when we are working in Photoshop. This is simple 1-bit black and white image. The second kind of image that we work with is the second one here, and notice that what we have here is more of a continuous tone image. In fact, it started out as a continuous tone image and we've converted it into pixels. When we look at this image we see all of these different shades of gray that we have in here. Many more shades of gray than we had in 1-bit black and white image. How many? Well, 0 to 255 or 256 shades of gray, going from 0 to pure black 255 to pure white.
Notice that we still have one channel there. The difference is the number of shades of gray that are captured and displayed here. But how to do that in machine and in an image and software that only understands 0 and 1 black and white? How do we do that? Well, what we do is we add more bits of information to everyone of those pixels. Let's take a look at the numbers behind these two images for a second. Let's talk about our 1- bit black and white image. Remember, one channel and what we have is two shades of gray, 1 bit of information.
So this is a 1-bit black and white image with one channel. Two shades of gray 1 bit for each one. For the 8-bit grayscale image how do we create that 256 shades of gray? Well, we take 2 times 2 is 4 times 2 is 8 times 2 is 16 times 2 is 32 times 2 is 64 times 2 is 128 times 2 is 256. That's 8 bits of information gives us 256 shades of gray. That's an 8-bit grayscale image. Again, we have one channel of 8-bit grayscale. So both images have one channel, the difference is this is eight times as much information, so 8 bits of information in every single channel.
Then the third fundamental type of image that we work with in terms of bit depth is the RGB color image. If you remember back from our discussion earlier in the course these are really imposter images in terms of color, aren't they? There is no such thing as color in a digital image, because our digital computers and digital images only understand what, grayscale, black and white. The color that we see here is actually created by the output device. in this case, the monitor that you're viewing. When we look at the individual channels that construct the image they're nothing but grayscale and when we zoom in on one of these channels what do we see, multiple shades of gray just like on the 8-bit grayscale image.
But in this case we have three channels and if you were to just look at this image right here and someone asked you, oh, what kind of image is that. You weren't looking at the Channels panel, you say, oh, that's an 8-big grayscale image, and guess what, you'd be right, and so is that and so is that. So if we have three channels with 8- bit grayscale, three times 8 is 24. That's where we get the concept of a 24-bit color image. So when we look at and we view the numbers for this, we see 256x256x256, 256 shades of gray for each of these channels, multiply those three out, you get 16.7 million colors.
You may have heard that number before, but now you know where it comes from. That gives us three 8-bit grayscale channels, 24-bit color, 3x8 is 24. And that's it. That's the fundamentals of bit depth. When we go into a scanning interface we are going to see choices like 1-bit or black and white or line art, those are all 1-bit terms. You'll see grayscale or 8-bits of grayscale and you may see 24-bit color and now you know what you're going to be choosing there. You're going to be choosing three 8-bit grayscale channels to create from your scanner. You may also see some other numbers like 32 or you may see 48-bit color and those are just devices that allow you to capture more than 8-bits of grayscale for every single channel.
So for instance, if you captured 16- bits of grayscale it would be 3 times 16 to 48 bits of grayscale on your RGB color image or twice as much information. More shades of gray, more tonal values. So if you want more total values in your image, then you add more bit depth to your image. You can go from 1 to 8 to 24 by adding more bit depth and more channels. Now just to cement this concept of bit depth and the kind of images we create at various bit depths with various numbers of channels, let's just do a quick review looking at some different images.
Let's just review what their bit depth and number of channels would be. How about this image here? What do you think this would be? Black and white, so 1-bit black and white and how many channels? One, Good! And how about this one, this beautiful portrait of Isaac, how many channels? One channel, bit depth would be 8-bits of grayscale. How many shades of gray? 256. Then this one our beautiful Santa portrait of Tina. How many channels? Remember, we've got RGB colors so it's going to be three channels. How many bits on each channel? 8, it gives us 256 shades of gray on each channel, 16.7 million colors.
3 times 8 bits is 24-bit color. For those of you who work in the print world, particularly the commercial print world you maybe sitting there thinking, all right, well, RGB is 24-bit color, but I print in CMYK. Well, let's just open this up as CMYK image in Photoshop and take a look at it and in the CMYK image, just like in an RGB where there is one channel per color, there is one channel per color here. So we have four 8-bit grayscale channels, and let's take a look. one for Cyan, one for Magenta, one for Yellow, and one for Black.
Each one has 8-bits of grayscale, you bet! This is a 32-bit CMYK image.
- Understanding grayscale values and channels
- Evaluating and correcting images with histograms
- Saving to different file formats
- Managing color
- Cleaning the scanner and images
- Reproducing versus assigning colors
- Recognizing contone versus dot pattern images
- Understanding bit depth
- Scanning logos and line art
- Scanning transparent film, positive or negative
- Capturing high dynamic range (HDR) scans