Abstract

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.

Proposed System

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.

Hardware Requirements:

• Hard disk : 40 GB
• RAM : 512 MB
• Processor Speed : 3.00GHz
• Processor : Pentium IV Processor

S/W System Configuration:-

• JDK 1.6
• Java Swing

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