ONLINE ADAPTIVE VECTOR QUANTIZATION WITH VARIABLE SIZE CODEBOOK ENTRIES

We present a new image compression algorithm that employs some of the most successful approaches to adaptive lossless compression to perform adaptive online (single pass) vector quantization with variable size codebook entries. We have tested this algorithm with a host of standar d test images (e.g., gray scale magazine images, medical images, space and scientific images, fingerprint images, and handwriting images) an d with no prior knowledge of the data or training, for a given fidelit y, the compression achieved typically equals or exceeds that of the JP EG standard. The only information that this algorithm needs in advance is the fidelity criterion. In addition, our algorithm is more flexibl e than standard VQ and provides tighter guarantees on fidelity.