Wavelet coding of images using trellis-coded quantization

Parthasarathy Sriram; Michael W. Marcellin

doi:10.1117/12.138469

1 October 1992 Wavelet coding of images using trellis-coded quantization

Parthasarathy Sriram, Michael W. Marcellin

Proceedings Volume 1705, Visual Information Processing; (1992) https://doi.org/10.1117/12.138469
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multiresolution approximations. An image is decomposed into a sequence of orthogonal components, the first being an approximation of the original image at some 'base' resolution. By the addition of successive (orthogonal) 'error' images, approximations of higher resolution are obtained. Trellis coded quantization (TCQ) is known as an effective scheme for quantizing memoryless sources with low to moderate complexity. The TCQ approach to data compression has led to some of the most effective source codes found to date for memoryless sources. In this work, we investigate the use of entropy-constrained TCQ for encoding wavelet coefficients at different bit rates. The lowest-resolution sub-image is quantized using a 2-D discrete cosine transform encoder. For encoding the 512 X 512, 8- bit, monochrome 'Lenna' image, a PSNR of 39.00 dB is obtained at an average bit rate of 0.89 bits/pixel.

Citation Download Citation

Parthasarathy Sriram and Michael W. Marcellin "Wavelet coding of images using trellis-coded quantization", Proc. SPIE 1705, Visual Information Processing, (1 October 1992); https://doi.org/10.1117/12.138469

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