pixelquantization

Pixel quantization is a process used in digital image processing to reduce the number of distinct colors in an image. This is often done to decrease file size, make images compatible with certain display technologies, or for artistic effect. In a digital image, each pixel has a specific color value. Quantization groups similar color values together and assigns them a single, representative color from a limited palette.

For example, a true-color image might use millions of colors, while a quantized image might be limited to 256 colors, 16 colors, or even just two colors (black and white). The reduction in color information leads to a smaller file size, as less data is needed to describe each pixel. However, this reduction can also lead to visual artifacts such as banding, dithering, or posterization, where smooth color gradients are replaced by distinct steps or patterns.

Various algorithms exist for pixel quantization, each with different approaches to selecting the representative colors and distributing them. Common methods include median cut, popularity algorithm, and octree quantization. The choice of algorithm can impact the visual quality of the quantized image and the degree of file size reduction achieved. Pixel quantization is frequently used in formats like GIF, which supports a limited color palette, and in applications where efficient storage and transmission of images are important.