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