TY - GEN
T1 - Image coding using wavelet transforms and entropy-constrained trellis coded quantization
AU - Sriram, Parthasarathy
AU - Marcellin, Michael W.
PY - 1993
Y1 - 1993
N2 - The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. Multi-resolution decomposition schemes have proven to be very effective for high-quality, low bit-rate image coding. In this work, we investigate the use of entropy-constrained trellis coded quantization for encoding the wavelet coefficients of both monochrome and color images. Excellent peak signal-to-noise ratios are obtained for encoding monochrome and color versions of the 512×512 `Lenna' Image. Comparisons with other results from the literature reveal that the proposed wavelet coder is quite competitive.
AB - The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. Multi-resolution decomposition schemes have proven to be very effective for high-quality, low bit-rate image coding. In this work, we investigate the use of entropy-constrained trellis coded quantization for encoding the wavelet coefficients of both monochrome and color images. Excellent peak signal-to-noise ratios are obtained for encoding monochrome and color versions of the 512×512 `Lenna' Image. Comparisons with other results from the literature reveal that the proposed wavelet coder is quite competitive.
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M3 - Conference contribution
SN - 0780309464
T3 - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
SP - V-554-V-557
BT - Image and Multidimensional Signal Processing
PB - Publ by IEEE
T2 - IEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5)
Y2 - 27 April 1993 through 30 April 1993
ER -