Classified block truncation coding-vector quantization: An edge sensitive image compression algorithm

摘要

Block truncation coding-vector quantization (BTC-VQ) is an extremely simple non-adaptive block-based image compression technique. It has a relatively low compression ratio; however, the simplicity of the algorithm makes it an attractive option. Its main drawback is the fact that the reconstructed pictures suffer from ragged edges. In this paper we show that by allowing the algorithm to adapt to the local picture statistics and by paying particular attention to the nature and reproduction of edges in the picture we are able to substantially improve the visual picture quality and at the same time allow for a moderate increase in the compression ratio.