Every image pixel on your computer monitor is a composite view of three channels Red, Green, and Blue. If the fineness of an image is your concern consider some time understanding bit-depth, color depth, and color gamut. So that you know what happens to an image while you make an edit, how much it can tolerate and how far you can go with certain types of files.
An image is made up of pixels and every pixel is represented by it pixel values. The range of pixels values determines the possibility and quality of an image.
A bit is a unit in the world of computing, represented by either 0 or 1. If you have an 8-bit RGB image, it contains 256 levels of gray in each channel Red, Green, and Blue. That means 256 x 256 x 256 or more than 16 million possible color values. So technically bit depth is the range of colors that represents your digital image.
Similarly, an image has a bit depth of 1 will hold only two possible colors: black and white. Or if you just convert your image from RGB mode to Grayscale mode it will contain only 256 gray values in it. Since the image has only one 8-bit grayscale channel in it.
Today’s high-end Digital SLRs are capable of capturing 12 bits of information or more. Probably you will work with images that have a bit depth of 16 or 65536 possible color values per channel. Or in case of your HDR (High Dynamic Range Image), it can be 32-bits per channel.
Photoshop’s Available Features for 16-Bit Images
Here is a list of tools and functions that Photoshop supports for 16-bbp images as Adobe documented it.
- Working in Grayscale, RGB Color, CMYK Color, Lab Color, and Multichannel modes.
- All tools in the toolbox, except the Art History Brush tool, can be used with 16‑bpc images.
- Color and tonal adjustment commands are available
- You can work with layers, including adjustment layers, in 16‑bpc images.
- Many Photoshop filters can be used with 16‑bpc images.
- To take advantage of certain Photoshop features, such as some filters, you can convert a 16‑bpc image to an 8‑bpc image. It’s best if you do a Save As and convert a copy of the image file so the original file retains the full 16‑bpc image data.
Bit Depth Determines the Range of Possible Colors
To simplify your understanding of bit depth I’ve created this simple table for your reference. It gives you the number of possible colors for each image with a certain bit depth.
|Bits Per Pixel||Range of Possible Colors|
On the left, you have the bit depth of your image starting from 1. A picture having a bit depth of 1 is also known as a bitmap image. A bitmap image is typically represented by two possible colors, black and white; it has no other shades of gray in between.
On the right, the table shows you the number of possible colors the bit depth on the left can produce.
Difference Between BPC and BPP
We encountered the acronyms BPC and BPP which often becomes very confusing. BPC stands for Bits Per Channel meaning range of color values of the individual channel. BPP stands for Bits Per Pixel meaning sum of the bits of all primary color channels that represent the range of color values of a pixel.
For example, an 8-bit RGB image has 256 color values in each channel; in other words, every pixel of an individual channel has 256 color possibilities. So the term is bits per channel. Where bits per pixel is the sum of the three channels that is 8 + 8 + 8 or 24 meaning the composite view of a pixel of the same image having 16777216 color possibilities.
Color depth refers to the number of color shades available on your display and is measured in bits per pixel (bpp). Typical ranges are 256 colors (8 bpp), thousands of colors (16 bpp), and millions of colors (32 bpp).
Color gamut is the range of colors of a color space. In-gamut colors mean reproducible colors and out-of-gamut colors mean colors that are not reproducible in a particular color space. The purity of the primaries is what determines the gamut for a device.
Whenever we perform an edit we posterize the image. Technically, posterization is a process of reducing the number of tones in an image. In an extream example, you may notice pixelated or jagged edges like staircases.
Now, you may be questioning; why should we posterize while we are learning about bit depth, color depth, and color gamut to preserve as many details as possible? The simplest answer I know is to compress the data that are beyond our perception to fit into the range that humans can perceive.
As we discussed the fineness of an image it is also necessary to understand the limits of our sensory perceptions. Because beyond that limit we are not able to distinguish and perceive the difference in tones and colors though there may be thousands and thousands of variations in theory.