Pel Adaptive Predictive Coding Based on Image Segmentation for Lossless Compression
Summary :
In this paper, we propose an adaptive predictive coding method based on image segmentation for lossless compression. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. Predictors of the MAR model can be adapted to changes in the local image statistics due to its local image processing. However, the performance of the MAR method is reduced when applied to images whose local statistics change within the block-by-block subdivided image. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder with each block. In order to enhance the compression performance, we improve the MAR coding method by using image segmentation. The proposed MAR predictor can be adapted to the local statistics of the image efficiently at each pixel. Furthermore, less side-information need be transmitted compared with the conventional MAR method.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.6 pp.1037-1046
- Publication Date
- 1999/06/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Digital Signal Processing
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Takayuki NAKACHI, Tatsuya FUJII, Junji SUZUKI, "Pel Adaptive Predictive Coding Based on Image Segmentation for Lossless Compression" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 6, pp. 1037-1046, June 1999, doi: .
Abstract: In this paper, we propose an adaptive predictive coding method based on image segmentation for lossless compression. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. Predictors of the MAR model can be adapted to changes in the local image statistics due to its local image processing. However, the performance of the MAR method is reduced when applied to images whose local statistics change within the block-by-block subdivided image. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder with each block. In order to enhance the compression performance, we improve the MAR coding method by using image segmentation. The proposed MAR predictor can be adapted to the local statistics of the image efficiently at each pixel. Furthermore, less side-information need be transmitted compared with the conventional MAR method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_6_1037/_p
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@ARTICLE{e82-a_6_1037,
author={Takayuki NAKACHI, Tatsuya FUJII, Junji SUZUKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Pel Adaptive Predictive Coding Based on Image Segmentation for Lossless Compression},
year={1999},
volume={E82-A},
number={6},
pages={1037-1046},
abstract={In this paper, we propose an adaptive predictive coding method based on image segmentation for lossless compression. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. Predictors of the MAR model can be adapted to changes in the local image statistics due to its local image processing. However, the performance of the MAR method is reduced when applied to images whose local statistics change within the block-by-block subdivided image. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder with each block. In order to enhance the compression performance, we improve the MAR coding method by using image segmentation. The proposed MAR predictor can be adapted to the local statistics of the image efficiently at each pixel. Furthermore, less side-information need be transmitted compared with the conventional MAR method.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Pel Adaptive Predictive Coding Based on Image Segmentation for Lossless Compression
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1037
EP - 1046
AU - Takayuki NAKACHI
AU - Tatsuya FUJII
AU - Junji SUZUKI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1999
AB - In this paper, we propose an adaptive predictive coding method based on image segmentation for lossless compression. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. Predictors of the MAR model can be adapted to changes in the local image statistics due to its local image processing. However, the performance of the MAR method is reduced when applied to images whose local statistics change within the block-by-block subdivided image. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder with each block. In order to enhance the compression performance, we improve the MAR coding method by using image segmentation. The proposed MAR predictor can be adapted to the local statistics of the image efficiently at each pixel. Furthermore, less side-information need be transmitted compared with the conventional MAR method.
ER -
English
