Python Data Analysis Cookbook

Quantizing colors

In ancient times, computer games were practically monochromatic. Many years later, the Internet allowed us to download images, but the Web was slow, so compact images with few colors were preferred. We can conclude that restricting the number of colors is traditional. Color is a dimension of images, so we can speak of dimensionality reduction if we remove colors from an image. The actual process is called color quantization.

Usually, we represent RGB (red, green, and blue) values in three-dimensional space for each pixel and then cluster the points. For each cluster, we are left with a corresponding average color. In this recipe, we will use k-means clustering (refer to the Clustering streaming data with Spark recipe), although ...