A fast color quantization algorithm using a set of one dimensional color intervals

In this study a robust color quantization method, which is based on a one-dimensional dynamic thresholding method, is introduced. The proposed method extracts a set of one-dimensional color intervals, each of which is ordered with respect to the distance to the reference color of that interval. The color intervals are then used to form the rows of the color similarity matrix for a given image. The selection of color palate is accomplished on the color similarity matrix by minimizing the total square error with respect to a threshold variable, which dynamically defines the color similarity for a given image. The experimental results indicate that the proposed method yields smaller quantization error and better visual appearance compared to the Heckbert's algorithm. It is faster than the existing color quantization methods.