Classic Tone Mapping Algorithms: Global and Local Mapping Approaches

This document discusses classic tone mapping algorithms, including both global and local mapping approaches. Tone mapping refers to computational methods that transfer color tonal characteristics from one image to another. In global mapping implementations, the entire image undergoes uniform tone transformation using histogram matching or color transfer functions applied to all pixels simultaneously. This approach is particularly effective when applying overall color characteristics from a reference image to a target image. Local mapping algorithms employ region-aware processing where different image segments receive customized tone adjustments based on spatial analysis, often using segmentation techniques or gradient-domain operations. Such methods are ideal for scenarios requiring selective tonal enhancements in specific image regions. From an implementation perspective, tone mapping algorithms typically involve color space conversion (e.g., to LAB or HSV), statistical analysis of color distributions, and pixel-wise transformation functions. These algorithms enable various artistic effects, such as colorizing grayscale photographs through reference-based color transfer or creating softer tonal renditions by adjusting contrast curves and saturation parameters.