DWT-based scene-adaptive color quantization

Abstract

Color quantization is the process of reducing the number of colors in an image. That is, color quantization maps a large number of colors into a much smaller number of representative colors while keeping color distortion to an acceptable level. The reduction in the number of colors lowers computational complexity associated with color processing, and achieves higher color image compression for storage and transmission purposes. The existing color quantization methods require that the number of representative or prominent colors be specified by the user. This paper presents a scene-adaptive color quantization method which eases this constraint by determining the number of representative colors automatically. This method utilizes the discrete wavelet transform to achieve a computationally efficient implementation of the multi-scale clustering algorithm in a 3D color space. The performance is evaluated in terms of compression ratio or number of representative colors, color distortion, and computational complexity. It is shown that the developed method outperforms the popular color quantization methods in terms of color distortion.