In this lesson video, we are going to cover about bit per channel and some basic information about high range images. If you open standard raster images such as PNG or JPG in any graphic applications, for example, Photoshop, GIMP or Krita, and then you zoomed in close enough, you will start to see the reality that these images are actually just a grid of small squares, which are called pixels. Each pixel stores at least three pieces of information, how much the strength is for the red color, how much is for the green color, and finally, how much is for the blue color. Different levels of red, green, and blue color components determine the color output of the pixel. These three types of information for each existing pixel are called channels. Basically, channel is just a block of data inside the pixel to hold the color combo So we have red channel, green channel and blue channel.

Now besides red, green and blue channels, we can also have alpha channel in our image. Essentially, alpha channel is an additional channel, which is used for controlling the transparency of each of the pixel. You must be aware though, that not all image file formats support alpha channel, PNG, Tiff, and TGA file formats are some of the examples that support alpha channel. So by using these file formats, you can have transparency because again, each pixels in the file can have four channels total, three channels for the color or the RGB values and one channel for transparency or the alpha channel. Okay, now we are going to discuss the nitty gritty of image file formats. And that will be the number of bits in each channel.

If you render something in Blender Try to save the render result to an image. You can see this color def, option eight, or 16. These numbers define the amount of bit per channel. Now you need to know that all standard images only use eight bit per channel. This is the setting for common images you see in the web, or images you see on screen devices such as TV, mobile phones, tablets, etc. Okay, so what is exactly bit per channel value means this number means that each channel in the image will have an eight bits memory slot.

So we have eight slots for red, eight slots for green and eight slots for blue. And if we have an alpha channel, then we have another eight slots for it. Okay. Now computers actually only know binary numbers which are zero and one. So these eight slots will be filled in with a bunch of zero and one numbers. For example, it can be something like this.

Now, these are just random digit numbers, just to give you an example. Okay? What we can count with the setup is that if we have eight probable space and two probable values, which are zero and one, how much are the total configurations that we can get from it? Well, that will be to power by eight equals to 256 variations. So with eight bits per channel, each channel can have one to 256 probable values. But if we start from zero instead of one, we can have zero to 255 values for each channel.

Now in blender, the RGB channels are all represented by zero to one scalar values, but behind the scene, each of these values is actually zero to 255. You can tell this because in other graphic software, so escrita for example, each of the channels red, green and blue can only have a maximum value of 255. Also, if we have an alpha channel, the level of transparency can exist from zero as the lowest value, which means fully transparent to 255, which means fully opaque. Okay, so for standard RGB file, each pixel will have eight plus eight plus eight bits equals to the total of 24 bits. But if you have an alpha channel in the image, each pixel will have an additional eight bits information. So the total will be 32 bits.

Now, although this seems not important at the moment, but trust me, by knowing this will help you understand file settings better in other graphic applications, because some graphic application has unique ways of showing image parameters, such as they ask you what To save as 24 bits or 32 bits, or save to RGB plus alpha, etc. By now you already understand that 24 bits image file equals to the standard RGB file with no transparency and 32 bits image file equals to a standard RGB file but with alpha transparency. Okay, so now we know that standard images have eight bits per channel, but what about other bits per channel value such as 16, or 32 bits per channel? Well, these types of images are mostly used to store more lighting information from the real world. You see, in the real world, lightness or brightness can range from zero to theoretically an infinite value.

Zero means a pitch black dark situation where there are no lights at all. In this condition, we are quote unquote blind s we cannot see anything Infinite brightness value is just a theory. As for us living on planet Earth, the brightest thing we can see is the sun. There is no man made light able to defeat the sun's brightness. Okay. Now if we need to capture this lightness information into an image, because our standard image only has eight bits per channel, it may only capture a small portion of the real world lighting condition.

We can however, compress it like this. This kind of technique is known as tone mapping. It is a very important technique because of our display devices such as computer monitors, TV, smartphone screens, etc. Even the LCD screen at the back of our digital cameras, mostly they all have a standard color space called sRGB, which stands for standard RGB sRGB only supports eight bits per channel. By the time I record this video, There are already some monitors that can display high range images, but they are still very expensive and so rarely used by common people. Now, tone mapping is good only for displaying images in display devices.

But if you want to reuse the image as a light source in a 3d scene, for example, or for further tweaking in post processing, eight bit per channel images are too limiting. There is not much of the actual light information that can be put in the image. That is why high range image formats were created to solve this problem. several examples of high range images or HDR, open xR, high range PNG files, Camera Roll files, etc. Essentially, these file formats able to store more than eight bits per channel. Now again, mostly these file formats are useless if we only want to see them directly with our standard screen or this display devices.

Because mostly our display devices can only support eight bits per channel. Therefore, they won't be able to show the true form of high range images. So again, to recap, high range images are mostly not useful for common people, but they are very useful for graphic professionals. For example, they can be used as light sources inside 3d software or inside game engines. Also, they are useful in photography and in video editing as they can provide more flexibility when you need to tweak the exposure.