Planning/scheduling techniques for VQ-based image compression

The enormous size of the data holding and the complexity of the information system resulting from the EOS system pose several challenges to computer scientists, one of which is data archival and dissemination. More than ninety percent of the data holdings of NASA is in the form of images which will be accessed by users across the computer networks. Accessing the image data in its full resolution creates data traffic problems. Image browsing using a lossy compression reduces this data traffic, as well as storage by factor of 30-40. Of the several image compression techniques, VQ is most appropriate for this application since the decompression of the VQ compressed images is a table lookup process which makes minimal additional demands on the user's computational resources. Lossy compression of image data needs expert level knowledge in general and is not straightforward to use. This is especially true in the case of VQ. It involves the selection of appropriate codebooks for a given data set and vector dimensions for each compression ratio, etc. A planning and scheduling system is described for using the VQ compression technique in the data access and ingest of raw satellite data.