Application of ‘most’ fuzzy linguistic quantifier to filter impulse noise

Original Research
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Abstract

Median filter is one of the established filters to de-noised impulse noise. Median filter determine median of a predefine mask. Sometimes estimated intensity of median filter again produces noise. Consider a pixel with 8-connected neighbors (255, 255, 255, 150, 255, 255, 100, 10, 90). If median filter is applied, then estimated intensity will be 255 i.e. 5th largest elements which is again noise. Hence in proposed work ‘at least half’, ‘as many as possible’, and ‘most’ fuzzy linguistic quantifier are used to de-noise images corrupted by impulse noise. In proposed work infrared image of ship with impulse noise is used as input. The impulse noise is inserted with a probability of 0.01. The ‘most’ quantifier produces more promising results than other two quantifiers. SNR ratio of proposed filter is much closer to original image as compare to median filter. Moreover, performance is verified for different types of images. Nevertheless, the performance of proposed method is found satisfactory.

Keywords

OWA Linguistic quantifier Impulse noise Median filter 

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Copyright information

© Bharati Vidyapeeth's Institute of Computer Applications and Management 2018

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringKrishna Institute of Engineering and TechnologyGhaziabadIndia
  2. 2.Department of Electronics EngineeringYMCA University of Science and TechnologyFaridabadIndia
  3. 3.Department of Electronics and Communication EngineeringNoida Institute of Engineering and TechnologyGreater NoidaIndia

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