a novel color image compression method using eigenimages

since the birth of multi–spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray–scale images, instead of an ensemble of an n–d realization. although, even now, some researchers make the same assumption, it is proved that using vector geometries leads to better results. in this paper, first a method is proposed to extract the eigenimages from a color image. then, using the energy compaction of the proposed method, a new color image compression method is proposed and analyzed. the proposed compression method, which uses vector–based operations, applies a grayscale compression algorithm on the eigenimages. experimental results show that, at the same bandwidth, the proposed method produce 3.6db and 1.9db enhancement in the quality, compared to jpeg and jpeg2000, respectively.