Entropy-constrained SBPVQ for image coding
Robert Alan Cohen, John W. Woods · International Conference on Acoustics, Speech, and Signal Processing · 2002
An entropy-constrained algorithm for a type of finite-state vector quantizer called sliding-block predictive vector quantization (SBPVQ) is presented. This coding algorithm searches small codebooks to achieve high performance at low coding rates. Results from training the coder on a set of monochrome images and then testing it on an image outside the training set are presented. Also, three parallel entropy-constrained SBPVQ coders are used to code 24-b/pixel color images. A total rate of less than 0.5 b/pixel is achieved with good performance by using this vector predictor variant.>