IEICE TRANSACTIONS on Communications
Quantization Noise Reduction for DCT Coded Images
Summary :
By modelling the quantization error as additive white noise in the transform domain, Wiener filter is used to reduce quantization noise for DCT coded images in DCT domain. Instead of deriving the spectrum of the transform coefficient, a DPCM loop is used to whiten the quantized DCT coefficients. The DPCM loop predicts the mean for each coefficient. By subtracting the mean, the quantized DCT coefficient is converted into the sum of prediction error and quantization noise. After the DPCM loop, the prediction error can be assumed uncorrelated to make the design of the subsequent Wiener filter easy. The Wiener filter is applied to remove the quantization noise to restore the prediction error. The original coefficient is reconstructed by adding the DPCM predicted mean with the restored prediction error. To increase the prediction accuracy, the decimated DCT coefficients in each subband are interpolated from the overlapped blocks.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E87-B No.8 pp.2342-2351
- Publication Date
- 2004/08/01
- Publicized
- Online ISSN
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- Type of Manuscript
- PAPER
- Category
- Multimedia Systems
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Ching-Chih KUO, Wen-Thong CHANG, "Quantization Noise Reduction for DCT Coded Images" in IEICE TRANSACTIONS on Communications,
vol. E87-B, no. 8, pp. 2342-2351, August 2004, doi: .
Abstract: By modelling the quantization error as additive white noise in the transform domain, Wiener filter is used to reduce quantization noise for DCT coded images in DCT domain. Instead of deriving the spectrum of the transform coefficient, a DPCM loop is used to whiten the quantized DCT coefficients. The DPCM loop predicts the mean for each coefficient. By subtracting the mean, the quantized DCT coefficient is converted into the sum of prediction error and quantization noise. After the DPCM loop, the prediction error can be assumed uncorrelated to make the design of the subsequent Wiener filter easy. The Wiener filter is applied to remove the quantization noise to restore the prediction error. The original coefficient is reconstructed by adding the DPCM predicted mean with the restored prediction error. To increase the prediction accuracy, the decimated DCT coefficients in each subband are interpolated from the overlapped blocks.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e87-b_8_2342/_p
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@ARTICLE{e87-b_8_2342,
author={Ching-Chih KUO, Wen-Thong CHANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Quantization Noise Reduction for DCT Coded Images},
year={2004},
volume={E87-B},
number={8},
pages={2342-2351},
abstract={By modelling the quantization error as additive white noise in the transform domain, Wiener filter is used to reduce quantization noise for DCT coded images in DCT domain. Instead of deriving the spectrum of the transform coefficient, a DPCM loop is used to whiten the quantized DCT coefficients. The DPCM loop predicts the mean for each coefficient. By subtracting the mean, the quantized DCT coefficient is converted into the sum of prediction error and quantization noise. After the DPCM loop, the prediction error can be assumed uncorrelated to make the design of the subsequent Wiener filter easy. The Wiener filter is applied to remove the quantization noise to restore the prediction error. The original coefficient is reconstructed by adding the DPCM predicted mean with the restored prediction error. To increase the prediction accuracy, the decimated DCT coefficients in each subband are interpolated from the overlapped blocks.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Quantization Noise Reduction for DCT Coded Images
T2 - IEICE TRANSACTIONS on Communications
SP - 2342
EP - 2351
AU - Ching-Chih KUO
AU - Wen-Thong CHANG
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E87-B
IS - 8
JA - IEICE TRANSACTIONS on Communications
Y1 - August 2004
AB - By modelling the quantization error as additive white noise in the transform domain, Wiener filter is used to reduce quantization noise for DCT coded images in DCT domain. Instead of deriving the spectrum of the transform coefficient, a DPCM loop is used to whiten the quantized DCT coefficients. The DPCM loop predicts the mean for each coefficient. By subtracting the mean, the quantized DCT coefficient is converted into the sum of prediction error and quantization noise. After the DPCM loop, the prediction error can be assumed uncorrelated to make the design of the subsequent Wiener filter easy. The Wiener filter is applied to remove the quantization noise to restore the prediction error. The original coefficient is reconstructed by adding the DPCM predicted mean with the restored prediction error. To increase the prediction accuracy, the decimated DCT coefficients in each subband are interpolated from the overlapped blocks.
ER -
English
