Two Stage Impulse Noise Removal Technique based on Neural Network and Fuzzy Decisions
Prachi C. Khanzode, S. A. Ladhake · 2011
Impulse Noise Reduction is very active research area in image processing. It is one of the important processes in the preprocessing of Digital Images. There are many techniques to remove the noise from the image and produce the clear visual of the image. Also there are several filters and image smoothing techniques available. All these available techniques have certain limitations. Recently, neural network are found to be very efficient tool for image Enhancement. In this, a two-stage noise removal technique to deal with impulse noise is proposed. In the first stage, an additive two-level neural network is applied to remove the noise cleanly and keep the uncorrupted information well. In the second stage, the fuzzy decision rules inspired by human visual system are proposed to compensate the blur of the edge and destruction caused by median filter. An neural network is proposed to enhance the sensitive regions with higher visual quality.