ICIC Express Letters Part B: Applications ICIC International c 2010 ISSN 2185-2766 Volume 1, Number 1, September 2010 pp. 9–14 DIRECTIONAL WEIGHTED MEDIAN BASED FUZZY FILTER FOR RANDOM-VALUED IMPULSE NOISE REMOVAL Ayyaz Hussain 1 , M. Arfan Jaffar 2 , Zia Ul-Qayyum 1 and Anwar M. Mirza 2 1 University Institute of Information Technology PMAS Arid Agriculture University Rawalpindi, Pakistan { ayyaz.hussain; ziaqayyum }@uaar.edu.pk 2 Department of Computer Science National University of Computer and Emerging Sciences FAST-NU, A. K. Brohi Road, H-11/4, Islamabad, Pakistan { arfan.jaffar; anwar.m.mirza }@nu.edu.pk Received May 2010; accepted July 2010 Abstract. Paper presents directional weighted median base fuzzy filter for random- valued impulse noise removal. In order to detect noise efficiently a fuzzy noise de- tection process is used whereas noise removal is performed by the directional weighted median based fuzzy filtering process. Proposed technique is compared with existing tech- niques based on peak-signal-to-noise-ratio (PSNR) and structural similarity index mea- sure (SSIM). Simulations show that the noise removal capability of the proposed technique is much better than the existing techniques. Keywords: Fuzzy filter, Random-valued impulse noise, Image restoration 1. Introduction. Image restoration is an important branch of image processing, which deals with the reconstruction of images by removing noise and blurriness and making them suitable for human perception [1]. Images can become corrupted during any of the acquisition, pre-processing, compression, transmission, storage and/or reproduction phases of the processing [2]. Liu and Li, in their reviews [3], have divided spatial image restoration techniques into two main categories namely conventional and blind image restoration. In conventional image restoration the information about the degradation process is generally known. This known information can be used to develop a model to restore the corrupted image back to its original form. Such techniques are used to solve motion blur, system distortions, geometrical degradations and additive noise problems. Unfortunately, in most cases, details about the degradation process are either partially or completely unknown, which make the image restoration process much more difficult. In the second category of image restoration [3], the image has to be restored directly from the degraded image without any prior information about the degradation process. Recently more focus has been placed on this category. One of the main tasks in developing such image restoration techniques is noise removal without destroying the image details. Noise smoothing and detail preservation are generally considered as conflicting tasks, because smoothing a region of the degraded image can potentially destroy an edge while sharpening edges may lead to the amplification of noise [4]. In the sequel, we present a directional weighted median base fuzzy filter (DWMFF) to removes random-valued impulse noise while preserving the edges and texture information. A number of approaches have been proposed for the impulse noise removal. Tukey [5], Astola et al. [6] and Pitas et al. [7] have utilized median filtering to remove impulse noise from the corrupted images. Other filters for removal of impulse noise includes histogram based fuzzy filter (HFF) [8], Lee et-al.’s novel fuzzy filter (NFF) [9], genetic 9