This paper proposes an Iterated Function System (IFS) which can reduce effects of quantization errors of the IFS parameters. The proposed method skips conventional analog-parameter search and directly selects optimum IFS parameters from pools of discrete IFS parameters. In conventional IFS-based image coding the IFS parameters are quantized after their analog optimum values are determined. The image reconstructed from the quantized parameters is degraded with errors that are traced back to quantization errors amplified in the iterated mappings. The effectiveness of this new realistic approach is demonstrated by simulation results over the conventional method.
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Hiroyuki HONDA, Miki HASEYAMA, Hideo KITAJIMA, "IFS Optimization Using Discrete Parameter Pools" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 2, pp. 233-241, February 2000, doi: .
Abstract: This paper proposes an Iterated Function System (IFS) which can reduce effects of quantization errors of the IFS parameters. The proposed method skips conventional analog-parameter search and directly selects optimum IFS parameters from pools of discrete IFS parameters. In conventional IFS-based image coding the IFS parameters are quantized after their analog optimum values are determined. The image reconstructed from the quantized parameters is degraded with errors that are traced back to quantization errors amplified in the iterated mappings. The effectiveness of this new realistic approach is demonstrated by simulation results over the conventional method.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_2_233/_p
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@ARTICLE{e83-d_2_233,
author={Hiroyuki HONDA, Miki HASEYAMA, Hideo KITAJIMA, },
journal={IEICE TRANSACTIONS on Information},
title={IFS Optimization Using Discrete Parameter Pools},
year={2000},
volume={E83-D},
number={2},
pages={233-241},
abstract={This paper proposes an Iterated Function System (IFS) which can reduce effects of quantization errors of the IFS parameters. The proposed method skips conventional analog-parameter search and directly selects optimum IFS parameters from pools of discrete IFS parameters. In conventional IFS-based image coding the IFS parameters are quantized after their analog optimum values are determined. The image reconstructed from the quantized parameters is degraded with errors that are traced back to quantization errors amplified in the iterated mappings. The effectiveness of this new realistic approach is demonstrated by simulation results over the conventional method.},
keywords={},
doi={},
ISSN={},
month={February},}
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TY - JOUR
TI - IFS Optimization Using Discrete Parameter Pools
T2 - IEICE TRANSACTIONS on Information
SP - 233
EP - 241
AU - Hiroyuki HONDA
AU - Miki HASEYAMA
AU - Hideo KITAJIMA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2000
AB - This paper proposes an Iterated Function System (IFS) which can reduce effects of quantization errors of the IFS parameters. The proposed method skips conventional analog-parameter search and directly selects optimum IFS parameters from pools of discrete IFS parameters. In conventional IFS-based image coding the IFS parameters are quantized after their analog optimum values are determined. The image reconstructed from the quantized parameters is degraded with errors that are traced back to quantization errors amplified in the iterated mappings. The effectiveness of this new realistic approach is demonstrated by simulation results over the conventional method.
ER -