A Fuzzy Impulse Noise Detection and Reduction Method

Abstract— Removing or reducing impulse noise is a very active
research area in image processing. In this paper we describe a
new algorithm that is especially developed for reducing all kinds
of impulse noise: FIDRM (Fuzzy Impulse noise Detection and
Reduction Method). It can also be applied to images having a
mixture of impulse noise and other types of noise. The result
is an image quasi without (or with very little) impulse noise
so that other filters can be used afterwards. This nonlinear
filtering technique contains two separated steps: an impulse
noise detection step and a reduction step that preserves edge
sharpness. Based on the concept of fuzzy gradient values our
detection method constructs a fuzzy set impulse noise. This
fuzzy set is represented by a membership function that will
be used by the filtering method, which is a fuzzy averaging
of neighbouring pixels. Experimental results show that FIDRM
provides a significant improvement on other existing filters.
FIDRM is not only very fast but also very effective for reducing
little as well as very high impulse noise.