Indexed colorspaces are a very useful way of reducing the amount of memory and space needed when you only need a certain number of colours. It is best explained by an example.
Let’s image you have a image in CMYK colour. That means you need 4 bytes to describe the colour of a pixel. If the image had 4,000 pixels, that would be 16,000 bytes.
Now, lets imagine that the image only used 255 colors. Instead of storing each pixel value, we could have a table with 256 entries (that is 1,024 bytes storing the 4 bytes for each CMYK color used) and then just store 1 byte per pixel to say which entry in the table to use. That would be a total of 4,000 bytes (for the colours) and 1,024 bytes for the look-up table. That is 5,024 bytes (quite a reduction from the 16,000 bytes.
And if we do not need 256 colours, we could do even better by squashing the bits together. If we only had 2 colours, we would still need 8 bytes for the look-up table but only a bit (one eighth of a byte) for each pixel to say which colour to use – a total of 508 bytes for everything!
This is what an indexed colorspace does. It allows us to store a table of colours in a look-up table and store the index, not the color. This reduces substantially the size of data needed. It works best with fewer colours so images with a huge number of colours do not gain as well and could actually take up more memory. But for appropriate images, 16,000 bytes to 508 bytes is a substantial size reduction.
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