The main objective of this system is to focus on fuzzy techniques for image filtering. Already several fuzzy filters for noise reduction have been developed. Those technique deals with fat-tailed noise like impulse noise. Most fuzzy techniques are not specifically designed for Gaussian (-like) noise or do not produce convincing results when applied to handle this type of noise. A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise.
The proposed system presents a new technique for filtering narrow-tailed and medium narrow-tailed noise by a fuzzy filter. The system:-
• First estimates a "fuzzy derivative" in order to be less sensitive to local variations due to image structures such as edges
• Second, the membership functions are adapted accordingly to the noise level to perform "fuzzy smoothing."
• For each pixel that is processed, the first stage computes a fuzzy derivative. Second, a set of 16 fuzzy rules is fired to determine a correction term. These rules make use of the fuzzy derivative as input.
• Fuzzy sets are employed to represent the properties. While the membership functions for and are fixed, the membership function for is adapted after each iteration.
Hard disk : 40 GB
RAM : 512 MB
Processor Speed : 3.00GHz
Processor : Pentium IV Processor
S/W System Configuration:-