TBM for color image processing: a quantization algorithm

In this paper, we propose a color image quantization algorithm based upon TBM. In this context, we consider that the color quantization problem can be viewed as clustering problem of the color-space into P clusters. Using TBM, we define a top-down evidential clustering algorithm which iteratively decreases the number of clusters of the color space into P clusters. This convergence is ensured using a novel criterion based upon the pignistic probability function. The P clusters provide the new reduced color palette and a quantized color image is computed. This quantization method is completely automatic and preserves the final result from any initial condition. Experiments on various images show the algorithm efficiency for color quantization and highlight the efficiency of TBM for color image processing