Activity index threshold classification in adaptive vector quantization

A method that addresses the problem of edge degradation in adaptive vector quantization is described. An index, the activity index A, based upon measurements of the input image data has been devised. This index is used to classify image areas into two groups, active and nonactive, according to whether A>T or A<T respectively; T is the threshold value for the activity index. For nonactive areas, large block size is used, while for active areas the block size is small. Two codebooks are generated corresponding to each of the two groups of blocks formed. A parametric expression for T has been heuristically derived for 4×4 blocks. Using this adaptive vector-quantization scheme, the results obtained have shown that the edge features are well-preserved on image reconstruction, while the computational effort has been significantly reduced