Vector Quantization Using Reflections of Triangular Subcodevectors

Abstract

The design of a codebook consisting of codevectors is the goal of vector quantization (VQ) schemes. This solution is not unique and many variants of VQ have been proposed. VQ suffers from computational and memory complexities that increase with the size of codebook and codevector dimensions. The lack of a universal codebook that works across different class of images necessitates the transmission of the codebook along with the codevector indices. This paper proposes a novel method of vector quantization using reflections of triangular subcodevectors. This method jointly reduces the memory and computational resources required for VQ. Numerical results are presented for the proposed scheme in comparison to a traditional VQ method and a method based on reflections

Related Papers

• A New Initial Codebook Algorithm of Learning Vector Quantization(2006)
• → Application of sorted codebook vector quantization to spectral coding of speech(2002)2 cited
• → Multiple stage vector quantization using competitive learning(2003)1 cited
• → Fast Vector Quantization Algorithm Based on Vector Features(2010)
• Comparative Study on the Application of LBG and SOFM in Image Vector Quantization(2010)