25-2 Study on Simple Image Compression by PCA of Clustered Color Areas

Abstract

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^*)