A novel adaptive fuzzy directional median filter is proposed in this paper which considers the directional pixels (horizontal, vertical and two diagonal directions) for estimation of adaptive threshold and incorporates the remaining background pixels based on directional statistics for efficient noise detection. The proposed filter consists of two phases: adaptive fuzzy noise detection phase followed by fuzzy filtering phase. In fuzzy noise detection phase, intensity differences from the central pixel in a 5×5 sliding window are calculated in four main directions, i.e., horizontal, vertical and two diagonal directions. Average value and central pixel value of 5×5 sliding window of newly constructed intensity differences image are exploited with fuzzy membership function to adaptively estimate threshold parameters. These parameters are then merged with fuzzy rules to detect the noise especially in detailed regions of an image. In filtering phase, simple median filter and directional median filters are smartly used based on edge and background information to restore the noisy pixels detected as noisy in adaptive fuzzy noise detection process. Experimental results based on well known quantitative measures shows the effectiveness of the proposed technique. center weighted median filter switching median filter directional weighted median filter adaptive median filter multi-stage directional median filter fuzzy reasoning based directional median filter design grey level of noisy pixel noise density intensity differences average directional differences average directional deviation of δ d central pixel value of average directional deviation of δ d membership degree membership degree of large first threshold parameter second threshold parameter median directional index 5×5 sliding window 
Adaptive threshold based fuzzy directional filter design using background information