IEICE TRANSACTIONS on Information
Performance Analysis and Comparison of Non-embedded and Embedded Wavelet Coders
Summary :
In this paper, we analyze wavelet-based coding in a rate-distortion (R-D) sense by using Laplacian and Markov models and verify the results with the performance of the typical embedded coders, EZW and SPIHT, and the non-embedded coder implemented here. Laplacian represents the probability density function (pdf) of wavelet coefficients and Markov statistical dependency within and among subbands. The models allow us to easily understand the behavior of a thresholding and quantization part and a lossless coding part and associate the embedded coders with the nonembedded coder, which is the point the paper approaches. The analytic results are shown to coincide well with the actual coding results.
- Publication
- IEICE TRANSACTIONS on Information Vol.E86-D No.6 pp.1103-1109
- Publication Date
- 2003/06/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing, Image Pattern Recognition
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Hyun Joo SO, Young Jun JUNG, Jong Seog KOH, Nam Chul KIM, "Performance Analysis and Comparison of Non-embedded and Embedded Wavelet Coders" in IEICE TRANSACTIONS on Information,
vol. E86-D, no. 6, pp. 1103-1109, June 2003, doi: .
Abstract: In this paper, we analyze wavelet-based coding in a rate-distortion (R-D) sense by using Laplacian and Markov models and verify the results with the performance of the typical embedded coders, EZW and SPIHT, and the non-embedded coder implemented here. Laplacian represents the probability density function (pdf) of wavelet coefficients and Markov statistical dependency within and among subbands. The models allow us to easily understand the behavior of a thresholding and quantization part and a lossless coding part and associate the embedded coders with the nonembedded coder, which is the point the paper approaches. The analytic results are shown to coincide well with the actual coding results.
URL: https://global.ieice.org/en_transactions/information/10.1587/e86-d_6_1103/_p
Copy
@ARTICLE{e86-d_6_1103,
author={Hyun Joo SO, Young Jun JUNG, Jong Seog KOH, Nam Chul KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Performance Analysis and Comparison of Non-embedded and Embedded Wavelet Coders},
year={2003},
volume={E86-D},
number={6},
pages={1103-1109},
abstract={In this paper, we analyze wavelet-based coding in a rate-distortion (R-D) sense by using Laplacian and Markov models and verify the results with the performance of the typical embedded coders, EZW and SPIHT, and the non-embedded coder implemented here. Laplacian represents the probability density function (pdf) of wavelet coefficients and Markov statistical dependency within and among subbands. The models allow us to easily understand the behavior of a thresholding and quantization part and a lossless coding part and associate the embedded coders with the nonembedded coder, which is the point the paper approaches. The analytic results are shown to coincide well with the actual coding results.},
keywords={},
doi={},
ISSN={},
month={June},}
Copy
TY - JOUR
TI - Performance Analysis and Comparison of Non-embedded and Embedded Wavelet Coders
T2 - IEICE TRANSACTIONS on Information
SP - 1103
EP - 1109
AU - Hyun Joo SO
AU - Young Jun JUNG
AU - Jong Seog KOH
AU - Nam Chul KIM
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2003
AB - In this paper, we analyze wavelet-based coding in a rate-distortion (R-D) sense by using Laplacian and Markov models and verify the results with the performance of the typical embedded coders, EZW and SPIHT, and the non-embedded coder implemented here. Laplacian represents the probability density function (pdf) of wavelet coefficients and Markov statistical dependency within and among subbands. The models allow us to easily understand the behavior of a thresholding and quantization part and a lossless coding part and associate the embedded coders with the nonembedded coder, which is the point the paper approaches. The analytic results are shown to coincide well with the actual coding results.
ER -
English
