Convergent algorithms for successive approximation vector quantisation with applications to wavelet image compression

Embedded wavelet coders have become very popular in image compression appli cations, owing to their simplicity and high coding efficiency Most of them incorporate some form of successive approximation scalar quantisation. Rece ntly developed algorithms for successive approximation vector quantisation have been shown to be capable of outperforming successive approximation sca lar quantisation ones. In the paper, some algorithms for successive approxi mation vector quantisation are analysed. Results that were previously known only on an experimental basis are derived analytically. An improved algori thm is also developed and is proved to be convergent. These algorithms are applied to the coding of wavelet coefficients of images. Experimental resul ts show that the improved algorithm is more stable in a rate x distortion s ense, while maintaining coding performances compatible with the state-of-th e-art.