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

Embedded wavelet coders have become very popular in image compression applications, owing to their simplicity and high coding efficiency. Most of them incorporate some form of successive approximation scalar quantisation. Recently developed algorithms for successive approximation vector quantisation have been shown to be capable of outperforming successive approximation scalar quantisation ones. In the paper, some algorithms for successive approximation vector quantisation are analysed. Results that were previously known only on an experimental basis are derived analytically. An improved algorithm is also developed and is proved to be convergent. These algorithms are applied to the coding of wavelet coefficients of images. Experimental results show that the improved algorithm is more stable in a rate×distortion sense, while maintaining coding performances compatible with the state-of-the-art