Progressive meshes transmission over a wired-to-wireless network
Wireless Networks
Image Wavelet Coding Systems: Part II of Set Partition Coding and Image Wavelet Coding Systems
Foundations and Trends in Signal Processing
On the statistics of matching pursuit angles
Signal Processing
Vector quantization in SPIHT image codec
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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A coding method for wavelet coefficients of images using vector quantization, called successive approximation vector quantization (SA-W-VQ) is proposed. In this method, each vector is coded by a series of vectors of decreasing magnitudes until a certain distortion level is reached. The successive approximation using vectors is analyzed, and conditions for convergence are derived. It is shown that lattice codebooks are an efficient tool for meeting these conditions without the need for very large codebooks. Regular lattices offer the extra advantage of fast encoding algorithms. In SA-W-VQ, distortion equalization of the wavelet coefficients can be achieved together with high compression ratio and precise bit-rate control. The performance of SA-W-VQ for still image coding is compared against some of the most successful image coding systems reported in the literature. The comparison shows that SA-W-VQ performs remarkably well at several bit rates and in various test images