Title :
Optimal vector transform for vector quantization
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fDate :
7/1/1994 12:00:00 AM
Abstract :
The vector transform has previously been proposed for vector quantization image coding. It is intended for decorrelating intervector dependency and preserving intravector dependency. The present authors study optimally such a transform. It is found that the optimal vector transform in the above senses, with the first-order Gaussian Markov model, does not exist unless the overall correlation matrix has an intervector and intravector decomposition structure. This is especially true for vectors formed by blocks of pixels. Then, a necessary and sufficient condition is derived for general vectors on the existence of their optimal vector transforms.<>
Keywords :
Markov processes; correlation theory; image coding; matrix algebra; optimisation; stochastic processes; transforms; vector quantisation; correlation matrix; decorrelation; first-order Gaussian Markov model; image coding; intervector decomposition structure; intervector dependency; intravector decomposition structure; intravector dependency; optimal vector transform; vector quantization; Decorrelation; Equations; Image coding; Karhunen-Loeve transforms; Matrix decomposition; Pixel; Stacking; Sufficient conditions; Vector quantization; Video coding;
Journal_Title :
Signal Processing Letters, IEEE