Marginal analysis prioritization for image compression based on a hierarchical wavelet decomposition
- 1 January 1993
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 5, 546-549 vol.5
- https://doi.org/10.1109/icassp.1993.319869
Abstract
A novel approach for jointly optimizing scalar quantization and tree-based quantization of hierarchical wavelet decompositions is presented. An image compression algorithm is developed around this approach, utilizing a pruned-tree image representation. Marginal analysis is applied to optimize jointly the pruned-tree representation and scalar quantization. Simulation results demonstrate that the proposed algorithm offer substantially improved signal-to-noise ratio at matching bit rates, compared with similarly structured compression algorithms.Keywords
This publication has 4 references indexed in Scilit:
- Image compression using the 2-D wavelet transformIEEE Transactions on Image Processing, 1992
- Image coding using wavelet transformIEEE Transactions on Image Processing, 1992
- An embedded wavelet hierarchical image coderPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Discrete Optimization Via Marginal AnalysisManagement Science, 1966