A two-stage method to improve the quality of quantized images

Abstract

This article proposes a color quantization strategy that combines two color quantization methods: Binary Splitting and Ant tree for Color Quantization. This solution combines a splitting method, which is faster, and a clustering-based method, which generates better quantized images. Given that time is a fundamental factor when considering a method for real-time applications, the proposed strategy attempts to exploit both of these methods for obtaining good quantized images with a low computational cost. The result of this approach not only generates better images than when Binary Splitting and Ant tree for Color Quantization are applied separately, but also helps to improve other methods frequently used for color quantization such as Wu’s method, Octree, Variance-based method and Neuquant.