Application of Type-2 Fuzzy Logic Filtering to Reduce Noise in Color Images Mehmet Emin Yüksel and Alper Bas‚türk Erciyes University, TURKEY © PHOTOLAB I. Introduction Abstract-In this paper, we present a novel application of type-2 fuzzy logic to the design of an image processing operator called an impulse detector. The type-2 fuzzy logic based impulse detector can be used to guide impulse noise removal filters to significantly improve their filtering performance and enhance their output images. The design of the proposed impulse detector is based on two 3-input 1-output first order Sugeno type interval type-2 fuzzy inference systems. The internal parameters of the type-2 fuzzy membership functions of the systems are determined by training. The performance of the impulse detector is evaluated by using it in combination with four popular impulse noise filters from the literature on four different popular test images under three different noise conditions. The results demonstrate that the type-2 fuzzy logic based impulse detector can be used as an efficient tool to effectively improve the performances of impulse noise filters and reduce the impulse noise undesirable distortion effects. O ne of the most common problems encountered during the acquisition and/or transmission of digital images is the contamination of the image with impulse noise. Due to this inevitable fact, the acquired or received digital image must usually be pre-processed by applying an appropriate filtering operator to the image to suppress the contaminating noise. The performance of this pre-filtering operation is of critical importance as the Digital Object Identifier 10.1109/MCI.2012.2200624 Date of publication: 12 July 2012 1556-603X/12/$31.00©2012IEEE AUGUST 2012 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 25