Fitri Utaminingrum, Keiichi Uchimura, Gou Koutaki
Digital image processing is often contaminated by more than one type of noise, such as mixed noise. In this paper, we propose a three-stage process to develop K-SVD method not only for reducing Gaussian noise but also for mixed Gaussian and impulse noise with optimizing input system and preserving edge structure. A three-stage process is combining of impulse noise removal, edge reconstruction and image smoothing. Press- ing of an impulse noise in the early stages by Decision Based Algorithm (DBA) and repairing edge structure by an edge-map are able to optimize the performance of the K-SVD method for smoothing an image. The performance of the filter is analysed in terms of Peak Signal to Noise Ratio (PSNR), Mean Structural Simi- larity (MSSIM) index and Blind Image Quality Index (BIQI). The simulation result is obtained a significant improvement over the previous research. Copyright © 2014 SCITEPRESS.
Computer Science and Electrical Engineering, Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto, 860-8555, Japan; Brawijaya University, Information Technology and Computer Science Programs, Jl. Veteran No.8 Malang, East-Java, 65145, Indonesia; Priority Organization for Innovation and Excellence, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto, 860-8555, Japan
