IEICE TRANSACTIONS on Fundamentals
Estimation of 2-D Noncausal AR Parameters for Image Restoration Using Genetic Algorithm
Summary :
Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.
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- IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.8 pp.1676-1682
- Publication Date
- 1998/08/25
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- Special Section PAPER (Special Section on Digital Signal Processing)
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Md.Mohsin MOLLAH, Takashi YAHAGI, "Estimation of 2-D Noncausal AR Parameters for Image Restoration Using Genetic Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E81-A, no. 8, pp. 1676-1682, August 1998, doi: .
Abstract: Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_8_1676/_p
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@ARTICLE{e81-a_8_1676,
author={Md.Mohsin MOLLAH, Takashi YAHAGI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Estimation of 2-D Noncausal AR Parameters for Image Restoration Using Genetic Algorithm},
year={1998},
volume={E81-A},
number={8},
pages={1676-1682},
abstract={Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Estimation of 2-D Noncausal AR Parameters for Image Restoration Using Genetic Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1676
EP - 1682
AU - Md.Mohsin MOLLAH
AU - Takashi YAHAGI
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 1998
AB - Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.
ER -
English
