Color image can be classified into different object areas with clustered color distribution. After the classification process, each object area is characterized by Principal Component Analysis. The a* and b* are predicted by the projection of L* onto chromatic plane using the eigen vectors of covariance matrix and the mean vectors. Finally, the full color image is reproducted by combining the luminance with (a*,b*).
