MedianCutQuantisierung

MedianCutQuantisierung is an algorithm used in image processing and computer graphics for color quantization. Its primary goal is to reduce the number of distinct colors in an image while minimizing the perceptual difference between the original and the quantized image. This is often done to save storage space or to prepare images for display on devices with limited color palettes.

The algorithm works by recursively partitioning the image's color space. It begins with a bounding box that encloses all the unique colors present in the image. At each step, the algorithm finds the median color along the longest dimension of the current color box. This median color is used to split the box into two smaller boxes. The process continues until a desired number of color boxes (and thus, a desired number of quantized colors) is reached.

Once the color space has been divided into the target number of boxes, a representative color is chosen for each box. Typically, the centroid of the colors within a box (the average of their RGB values) is used as the representative color. When quantizing the original image, each pixel's color is replaced by the representative color of the box it falls into. This results in an image with a reduced color palette, where similar original colors are mapped to a single representative color. MedianCutQuantisierung is known for producing relatively good results with a moderate computational cost.