 So we have two terms to discuss today. Histogram and bit depth. And they are related. And let's start with bit depth. And first a bit of trivia for you. Bit is short for binary information digit. Not quite an acronym, but I guess close enough. And bits are fundamental to how computers work. And they're also the building block of all digital information. All the videos, photos, and texts you see on a computer screen are really just zeros and ones, bits. The important thing for this video is what we mean by bit depth when it comes to images on a screen. And let's start with a bit depth of one. A bit depth of one means you just have a single bit to work with. So we only have two states or two brightness values to make the image. Zero, which means fully off or black and one, which means the pixel would be fully on or saturated. And you may be thinking, why are you starting with such a basic example? No camera works that way. Well, maybe so. But I'm old enough to remember that the first computer I used had a display that I think really had a bit depth of one. Any pixel on the display could only be off or on zero or one. And it was green because they used a green phosphor in the cathode ray tube for some reason. Anyways, if we move on to a bit depth of two, we get four values to work with. If we move on to a bit depth of three, we get eight brightness values to work with. You see how this is working because we do two to the power of whatever the depth is. So three bit depth, I mean two to the power of three, we get eight brightness values. So let's stop at this point and look how we make a histogram, which is just a chart that displays how dark or bright every pixel in a digital image is. So I'm going to get a bit creative here. And I'm going to make a very basic image out of cups of tea. And in terms of a digital image, you can think of each cup of tea as being one pixel in the image. And I'm actually basing this on what a small star looks like really zoomed in. All right, and there we go. So now let's rearrange these cups into a three bit histogram. On the x-axis, we go from zero to seven because we get eight values to work with from a bit depth of three. And on a histogram, the y-axis is just a count of how many pixels we have at each brightness value. So let's put these side by side now and let it sink in what the histogram is really telling us. It's telling us the number of pixels at each brightness value based on the bit depth of the image. In this case, it's a three bit image. Let's jump up now to a bit depth of eight. This is the usual histogram you see on a camera screen or in Photoshop. And eight bits is also the standard for JPEGs video, basically anything you see on the web. So with eight bits, we get 256 possible brightness values because two to the power of eight is 256. On an image histogram, zero is still black while white is fully saturated and that's now 255. Middle gray is at like 128. Now, you may be thinking at this point, this doesn't seem like enough, just 255 values to fully represent a photo. But so far in this video, we've just been talking gray scale. Well, what is called true color in an image is red, green and blue. And each of those channels gets 256 possible values. So that's what it means when Photoshop says eight bits per channel, the channels are red, green and blue. And to arrive at the total number of possible colors from red, green and blue, each getting eight bits to work with, we would multiply 256 by 256 by 256 by 256 to arrive at 16,777,216 possible color variations, which for most kinds of images is plenty to accurately represent the scene. The reason we often use a bit depth of 16 or 32 and ask to photography is because we're stacking many images together, which adds precision and we do this while the image is still in the linear space where the histogram is compressed and bunched up over to the left hand side. And then with that added precision, it's going to be very helpful when we stretch the image out, which really opens up the mid tones and spreads them out, creating contrast and very importantly separation, which helps bring the dim nebula or galaxy out from the sky, which in truth is usually pretty close to the same brightness value as the deep sky object. But stacking adds that precision and then we can stretch it out. Well, I'm not a time I'm sure I'll do follow ups because there's tons to say about bit depth histograms. So drop your questions in the comments. This has been Nico Carver with another five minute Friday. Clear skies.