Publication: Noise level reduction of 2-d signal using fuzzy logic
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Date
2007-03-01
Authors
Tan, Chau Wei
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Abstract
The increasing popularity of automated visual inspection system for manufacturing process has demonstrated the increasing importance of digital image processing in industrial area. As a major branch in image processing, the needs for perfect digital noise removal filter are receiving more and more attentions. Instead of conventional noise removal techniques, researchers have made their move into non-linear noise removal techniques. The objective of this project is to design a non-linear digital filter that is capable to reduce noise level in digital signals while preserving features and structures of the original signals. Fuzzy image processing, a term that reveals the applications of fuzzy logic into image processing, is an image processing technique in which fuzzy membership functions are used to decide the actions to be taken in handling noise. In this dissertation, a Multipass Fuzzy Filter is proposed. The proposed filter is a feature preserving and perfect noise removal filter, adapting an impulse noise membership function and a proposed uniform noise membership function. The filter consists of three blocks, each block designed with membership functions for different type noise removal. First, the noisy image is processed by the first block where impulse noise is removed. Then, the output is feed to the second block for uniform noise removal. The output is then processed by the third block which acts as a correction module. Mean square error (MSE) has been used to measure the performance of the filter. The experimental results has clearly demonstrated that the proposed fuzzy filter is capable of removing impulse and uniform noise efficiently while preserving details and textures in image that are intensively corrupted.