The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Space-frequency quantization for wavelet image coding
Abstract
A new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation. This paper addresses the problem of how spatial quantization modes and standard scalar quantization can be applied in a jointly optimal fashion in an image coder. We consider zerotree quantization (zeroing out tree-structured sets of wavelet coefficients) and the simplest form of scalar quantization (a single common uniform scalar quantizer applied to all nonzeroed coefficients), and we formalize the problem of optimizing their joint application. We develop an image coding algorithm for solving the resulting optimization problem. Despite the basic form of the two quantizers considered, the resulting algorithm demonstrates coding performance that is competitive, often outperforming the very best coding algorithms in the literature.
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Cites
A theory for multiresolution signal decomposition: the wavelet representation
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Daubechies, I. (1988) · Communications on Pure and Applied Mathematics · doi:10.1002/cpa.3160410705 · Cited by 8,190
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Gersho, A., & Gray, R. M. (1992) · Springer eBooks · doi:10.1007/978-1-4615-3626-0 · Cited by 7,003
The Laplacian pyramid as a compact image code
Burt, P., & Adelson, E. (1983) · IEEE Transactions on Communications · doi:10.1109/tcom.1983.1095851 · Cited by 6,077
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
Said, A., & Pearlman, W. A. (1996) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/76.499834 · Cited by 5,353
Embedded image coding using zerotrees of wavelet coefficients
Shapiro, J. M. (1993) · IEEE Transactions on Signal Processing · doi:10.1109/78.258085 · Cited by 4,815
Image coding using wavelet transform
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Entropy-based algorithms for best basis selection
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Arithmetic coding for data compression
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Cited by
Directionlets: anisotropic multidirectional representation with separable filtering
Velisavljevic, V., Beferull-Lozano, B., Vetterli, M., & Dragotti, P. L. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.877076 · Cited by 326
Distributed Compressed Sensing
Coluccia, G., Ravazzi, C., & Magli, E. (2015) · SpringerBriefs in Electrical and Computer Engineering · doi:10.1007/978-981-287-390-3_2 · Cited by 323
Signal recovery from random projections
Candes, E. J., & Romberg, J. K. (2005) · SPIE Proceedings · doi:10.1117/12.600722 · Cited by 299
Metadata
- Authors
- Xiong, Z., Ramchandran, K., & Orchard, M. T.
- Venue
- IEEE Transactions on Image Processing
- Published
- 1997-05
- Volume
- 6
- Issue
- 5
- Pages
- 677-693
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2163935396
- Cited by
- 366
- References
- 26
- FWCI
- 34.46
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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