An Image Restoration Method Using IFS

Miki Haseyama, Megumi Takezawa, Keiko Kondo, Hideo Kitajima

Abstract: This paper proposes a new image restoration method based on the iterated function system (IFS). The proposed method can restore images contaminated by impulsive noise according to self-similarity represented by the IFS parameters. Since the IFS is usually used for image coding, it has never been applied to image restoration; and it cannot be utilized for image restoration as it is. In order to adapt the IFS for image restoration, this paper reforms the conventional criterion for the computation of the IFS parameters to suit for image restoration, and as preprocessing we apply an /spl epsiv/-filter in which a median filter is embedded to contaminated images prior to computing the IFS parameters. Some simulation results are presented to demonstrate the effectiveness of this method.