Transform image coding using broad vector quantization

Abstract

An adaptive discrete cosine transform (DCT) method for image compression is presented. Clustering technique based on vector quantization (VQ) is used to reconstruct binary patterns representing the location maps of selected DCT coefficients. The DCT of image blocks are classified into broad categories and after quantization, the transform coefficients are encoded using a variable word length (VWL) coding scheme. It is demonstrated that this approach is well-suited for real-time visual communications systems, and performs efficiently at very low bit rates.