A new approach of color image quantization based on Normalized Cut algorithm

This paper presents a novel color quantization method based on Normalized Cut clustering algorithm, in order to generate a quantized image with the minimum loss of information and the maximum compression ratio, which benefits the storage and transmission of the color image. This new method uses a deformed Median Cut algorithm as a coarse partition of color pixels in the RGB color space, and then take the average color of each partition as the representative color of a node to construct a condensed graph. By employing the Normalized Cut clustering algorithm, we could get the palette with defined color number, and then reconstruct the quantized image. Experiments on common used test images demonstrate that our method is very competitive with state-of-the-art color quantization methods in terms of image quality, compression ratio and computation time.