DocumentCode :
2156718
Title :
Image modeling and restoration: a genetic approach
Author :
Mollah, Md Mohsin ; Yahagi, Takashi ; Lu, Jianming
Author_Institution :
Graduate Sch. of Sci. & Technol., Chiba Univ., Japan
Volume :
2
fYear :
1997
fDate :
20-22 Aug 1997
Firstpage :
1006
Abstract :
The least-squares (LS) estimates of a noncausal autoregressive (NCAR) system leads to a biased solution. In this paper, an unbiased solution of 2-D NCAR system is formulated for both a noiseless and a noisy situations. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed. An application to the image restoration process when the image is corrupted by additive observation noise of unknown noise variance is also presented
Keywords :
Gaussian noise; autoregressive processes; genetic algorithms; image restoration; least squares approximations; parameter estimation; white noise; 2D noncausal autoregressive system; additive observation white Gaussian noise; genetic algorithm; image modeling; image restoration; least squares estimates; multiobjective function; noise variance; noiseless situations; noisy situations; unbiased solution; Additive noise; Degradation; Gaussian noise; Genetic algorithms; Image processing; Image restoration; Mathematical model; Maximum likelihood estimation; Parameter estimation; Parametric statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computers and Signal Processing, 1997. 10 Years PACRIM 1987-1997 - Networking the Pacific Rim. 1997 IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-3905-3
Type :
conf
DOI :
10.1109/PACRIM.1997.620430
Filename :
620430
Link To Document :
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