Successive approximation vector quantization with improved convergence
Eduardo A. B. da Silva, Marcos Craizer · 2002
Successive approximation vector quantization (SA-VQ) is a relatively recent algorithm in which each vector is represented by a series of vectors of decreasing magnitudes and orientations drawn from a fixed orientation codebook. It has been shown to provide good performance in wavelet coding schemes. In this paper, analytical results concerning the convergence of SA-VQ are presented in the form of two theorems. In the first one, results which had been previously determined only experimentally are presented analytically. In the second, a modification is proposed to the original SA-VQ algorithm which improves its convergence properties. Then, image compression results deriving from the application of the modified SA-VQ algorithm to coding wavelet transform coefficients are presented, showing improved PSNR performance.