Normalizing RGB values: The technical debate between dividing by 255 vs 256 in image processing

Summary

This article explores the technical debate around normalizing RGB pixel values when converting from 8-bit integers (0-255) to floating point for image processing. It compares two approaches: dividing by 255 (standard method) versus dividing by 256 (alternative method). The article explains the mathematical reasoning behind each approach, including considerations for rounding errors, quantization effects, and the implications for image processing accuracy. It provides code examples in Python/NumPy and discusses the trade-offs between the two methods, ultimately helping developers understand which approach is more appropriate for different image processing scenarios.