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Y. Y. Li, F.-L. Chung and S. T. Wang, “A Robust Neurofuzzy Network Approach to Impulse Noise Filtering for Color Images,” Applied Soft Computing, Vol. 8, No. 2, 2008, pp. 872-884.

has been cited by the following article:

• TITLE: Accurate Tools for Analyzing the Behavior of Impulse Noise Reduction Filters in Color Images

  AUTHORS: Fabrizio Russo

  KEYWORDS: Color Image Denoising; Image Analysis; Vector Filters; Impulse Noise

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.4 No.1, February 27, 2013

  ABSTRACT: Effective cancellation of noise and preservation of color/structural information are features of paramount importance for any filter devoted to impulse noise removal in color images. In this paper novel full-reference tools for analyzing the behavior of this family of filters are presented. The proposed approach is based on the classification of color errors into two main classes that separately take into account the inaccuracy in removing noise pulses and the filtering distortion. The distortion errors are then classified into two subclasses for a deeper analysis of the filtering behavior. Computer simulations show that the proposed method gives more accurate results than using other measures of filtering performance in the literature. Furthermore, the method can easily yield the spatial location of the different filtering features in the image.