Rate-distortion efficiency of subband coding with integer coefficient filters
Discusses efficient image compression algorithms that are suitable for low-complexity implementation in deep space probes. Subband coding or equivalent wavelet transforms provide some advantages over traditional block transforms in terms of rate distortion performance under the mean square-error cri...
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| Published in | Proceedings Nineteen Ninety-Four IEEE International Symposium on Information Theory p. 419 |
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| Main Authors | , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
1994
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| Subjects | |
| Online Access | Get full text |
| ISBN | 0780320158 9780780320154 |
| DOI | 10.1109/ISIT.1994.395034 |
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| Summary: | Discusses efficient image compression algorithms that are suitable for low-complexity implementation in deep space probes. Subband coding or equivalent wavelet transforms provide some advantages over traditional block transforms in terms of rate distortion performance under the mean square-error criterion and according to subjective visual evaluation. Furthermore, the possibility of choosing a desired resolution, independently in the time or frequency domain, is important to preserve the specific features that are most relevant for substantiating scientific findings. A low-complexity version of a JPEG-like algorithm based on the integer cosine transform (ICT), is being implemented in software on the Galileo spacecraft. The most promising candidate for improving the current ICT-based algorithm is a subband coding method that uses quadrature mirror filters (QMF) with lattice structure and integer coefficients. Lattice QMF filters are paraunitary perfect reconstruction (PR) filters. This provides a simple method to obtain PR filters with integer coefficients, without the need for any additional constraint to be satisfied for guaranteeing the PR property. Similarly, orthonormal wavelet transforms can be easily implemented by de signing a two-channel paraunitary QMF bank and then using a tree structure. This means that the wavelet orthonormality properties can be retained even when the coefficients are quantized or subject to certain constraints.< > |
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| ISBN: | 0780320158 9780780320154 |
| DOI: | 10.1109/ISIT.1994.395034 |