bchao1 / quantization

Color quantization zoo.

color-quantization

Color quantization zoo.

This is a repository for exploring various color quantization methods. Algorithm implementations are in src/, with great help from numpy.

Table of Contents

• Otsu's Method
• Median Cut
• Kmeans++
• Octree
• Floyd-Steinberg Dithering

Otsu's method - binarization

Otsu's method is an algorithm for color binarization. See src/otsu/.

Colored	Otsu's method	Median threshold

Median cut - quantization

Median cut is an algorithm for color quantization of images into 2ⁿ colors. See src/median_cut/.

Original	2 color
4 color	8 color
16 color	32 color
64 color	128 color

K-means++ - quantization

K-means++ is an improved K-means algorithm with better initialization. Initializing with sparser centroids (though more computationally expensive) can lead to faster convergence. Note that this algorithm can quantize an image to arbitrary number of colors. See src/kmeans/.

Original	2 color
3 color	5 color
10 color	20 color
50 color	100 color

Octree - quantization

Octrees are trees which each node has (at most) eight children. It is an effective data structure for partitioning 3-dimensional spaces. A great post on octree implementations (in JavaScript) for color quantization can be found here.

Floyd-Steinberg Dithering

Dither is an intentionally applied form of noise used to randomize quantization error, preventing large-scale patterns such as color banding in images. See src/dithering/.

Original	64-colored	Dithered