Vector quantization and signal compression
Vector quantization and signal compression
Handbook of Image and Video Processing
Handbook of Image and Video Processing
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Advances in residual vector quantization: a review
IEEE Transactions on Image Processing
A successive approximation vector quantizer for wavelet transform image coding
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Vector SPIHT for embedded wavelet video and image coding
IEEE Transactions on Circuits and Systems for Video Technology
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The image coding algorithm “Set Partitioning in Hierarchical Trees (SPIHT)” introduced by Said and Pearlman achieved an excellent rate-distortion performance by an efficient ordering of wavelet coefficients into subsets and bit plane quantization of significant coefficients. We observe that there is high correlation among the significant coefficients in each SPIHT pass. Hence, in this paper we propose trained scalar-vector quantization (depending on a boundary threshold) of significant coefficients to exploit correlation. In each pass, the decoder reconstructs coefficients with scalar or vector quantized values rather than with bit plane quantized values. Our coding method outperforms the scalar SPIHT coding in the high bit-rate region for standard test images.