The Journal of Analysis

, Volume 27, Issue 1, pp 89–102 | Cite as

Fuzzy logic and distance measure based adaptive fixed value impulse noise filter

  • P. S. Eliahim Jeevaraj
  • P. ShanmugavadivuEmail author
Original Research Paper


The proposed Fuzzy Logic and Distance Measure based Adaptive Filter (FDMA) uses the principles of fuzzy logic and distance measure for the detection and correction of fixed-value impulse noise, respectively. This filter, in the noise detection phase, classifies the pixel of the corrupted image either as uncorrupted or corrupted ones, using fuzzy logic and statistical measures and thereby constructs a flag matrix. In the noise correction phase, the intensity of each corrupted pixel is replaced by an estimated intensity value, computed using its uncorrupted neighbouring pixel, lying within Minimum Euclidian Distance. The noise suppression capability of this filter is quantitatively measured using Peak Signal to Noise Ratio, Mean Structural Similarity Index Matrix and Coefficient of Correlation values. Additionally, the merit of this filter is endorsed by Human Visual Perception of the restored images. The noise restoration ability of FDMA is confirmed to outperform the reported filters. This filter can seamlessly be employed in the application domain wherein fixed-value impulse noise is the primary cause for quality degradation.


Noise detection Noise correction Fuzzy systems Euclidian distance Fixed-value impulse noise 

Mathematics Subject Classification

68U10 94A08 



The Authors wish to place on record the financial assistance received in the form of a Major Research Project from UGC, New Delhi. The authors also thank the authorities of GRI for their support.


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Copyright information

© Forum D'Analystes, Chennai 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceBishop Heber CollegeTiruchirappalliIndia
  2. 2.Department of Computer Science and ApplicationsGandhigram Rural Institute – Deemed to be UniversityGandhigramIndia

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