A GREEDY TREE GROWING ALGORITHM FOR THE DESIGN OF VARIABLE-RATE VECTOR QUANTIZERS

The performance of vector quantization for image compression can be improved by using a variable rate code which is able to devote more bits to regions of an image that are active or difficult to code, and fewer bits to less active regions. We present a technique for directly designing a variable rate tree-structured vector quantizer by growing the tree one node at a time rather than growing the tree one layer at a time as is more common. The technique is a natural extension of a tree growing method for decision trees. When the tree is pruned with a recently generalized algorithm for optimally pruning trees, improvement is measured in the signal-to-noise ratio at high rates over pruning a fixed rate tree-structured vector quantizer of the same initial rate. The growing algorithm can be interpreted as a constrained inverse of the pruning algorithm.