Multiresolution Vector Quantization

Multiple Description Lattice Vector Quantization Multiple Description Lattice Vector Quantization

This thesis studies the multiple description vector quantization with lattice codebooks (MDLVQ). The design of index assignment is crucial to the performance of MDLVQ. However, to our best knowledge, none of previous index assignment algorithms for MDLVQ is optimal. In this thesis, we propose a simple linear-time index assignment algorithm for MDLVQ with any K ≥ 2 balanced descriptions. We prov...

Extension of two-stage vector quantization-lattice vector quantization

This paper is the extension of two-stage vector quantization–(spherical) lattice vector quantization (VQ–(S)LVQ) recently introduced by Pan and Fischer [1]. First, according to high resolution quantization theory, generalized vector quantization–lattice vector quantization (G-VQ–LVQ) is formulated in order to release the constraint of the spherical boundary for the second-stage lattice vector q...

Vector Quantization for Image Compression-Concept Quantization

Entropy-constrained Vector Quantization

| Entropy-constrained vector quantization (ECVQ) 3] offers substantially improved image quality over vector quan-tization (VQ) at the cost of additional encoding complexity. We extend results in the literature for fast nearest neighbor search of VQ to ECVQ. We use a new, easily computed distance that successfully eliminates most codewords from consideration.

Entropy-constrained vector quantization

Akfmct-An iterative descent algorithm based on a Lagrangian formulation is introduced for designing vector quantizers having minimum distortion subject to an entropy constraint. These entropy-constrained vector quantizers (ECVQ’s) can be used in tandem with variable rate noiseless coding systems to provide locally optimal variable rate block source coding with respect to a fidelity criterion. E...