Optimization of vector quantization for large color images

Images are produced to record and store infomiation that people want to preserve. As a matter of fact, visual informadon is more easily accepted and understood than other types of informadon, for example, linguistic information, and thus has become a popular way of representing information. However, compared to other types of information processing, images contain much more data and usually takes more processing time and storage space. With more and more wide use of computers and the Intemet, efficient methods of image transmission and storage are needed because of the limitation of the currently available speed of the Intemet. In other applications, such as medical image transmission and storage, video conferencing. Video On Demand (VOD) systems, where huge amounts of image data storage or fast, real-time image transmission are demanded, image compression can provide a major solution.

Image compression involves identification of the redundancy of the information contained in images so as to reduce the amount of data to represent the original image, thus achieving a lower bit rate, less transmission time and storage space.