Advances in residual vector quantization: a review
Related Experiment Video
Updated: Jul 7, 2026

High-speed Particle Image Velocimetry Near Surfaces
Published on: June 24, 2013
C F Barnes1, S A Rizvi, N M Nasrabadi
1Georgia Tech. Res. Inst., Georgia Inst. of Technol., Atlanta, GA.
Abstract:
Advances in residual vector quantization (RVQ) are surveyed. Definitions of joint encoder optimality and joint decoder optimality are discussed. Design techniques for RVQs with large numbers of stages and generally different encoder and decoder codebooks are elaborated and extended. Fixed-rate RVQs, and variable-rate RVQs that employ entropy coding are examined. Predictive and finite state RVQs designed and integrated into neural-network based source coding structures are revisited. Successive approximation RVQs that achieve embedded and refinable coding are reviewed. A new type of successive approximation RVQ that varies the instantaneous block rate by using different numbers of stages on different blocks is introduced and applied to image waveforms, and a scalar version of the new residual quantizer is applied to image subbands in an embedded wavelet transform coding system.
Related Concept Videos
Vector Algebra: Method of Components
In many applications, the magnitudes and directions of...
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Introduction to Vector Functions
Conservative Vector Fields
Vector Representation of Complex Numbers
Consider a function defined as the product of the complex factors in the numerator divided by the product of the complex factors in the denominator.
Position and Displacement Vectors
Further, several important kinds of...