Should you normalize RGB values by 255 or 256?
This article explores the technical debate regarding whether RGB values should be normalized by 255 or 256 during image processing. It analyzes the mathematical implications of both methods, specifically regarding how they map integer values to floating-point ranges.
Why it matters
Understanding these normalization methods is critical for developers working on image processing pipelines to ensure color accuracy and consistency.
Let’s say you’re writing an image processing program. The program takes in an image, converts it to floating point, does some processing and finally saves the modified pixels to disk as 8-bit colors. The question today concerns how exactly the integer-to-float conversion should be done. There are two approaches which, written in Python and NumPy, look like this:
The content is a technical discussion on programming methodology with no political or social bias.
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