A Novel Rank Order Mean-Based Switching Scheme for the Removal of Impulse Noises in Images
| Autor: | Ming-Yuan Li, 李銘元 |
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| Rok vydání: | 2005 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 93 During image transmission, digital images are frequently corrupted by noises. Among them, the impulse noise is frequently seen. Different kinds of linear and nonlinear filters have been proposed to remove impulse noises. In recent years, nonlinear filters gradually substituted linear filter in the application of removing impulsive noises. In this thesis, we combine one kind of the nonlinear filter, the median filter, and the fuzzy rules to develop a novel rank order filter mean based switching scheme (NROM-SS) to remove the impulse noises from the images. While realizing the fuzzy system, it is of most difficulty to find out the fuzzy characteristic. In this study, the fuzzy characteristic is derived based on the differences defined between the current pixel and the rank order value. Specifically, the Laplacian edge detection is also used to produce the fuzzy measurement. Moreover, in order to control the dynamic range of weights of defuzzifier, the weights are optimized using constrained LMS (least mean square) and genie algorithm. In the design of experiments, 10% to 30% of the low-amplitude uniform-valued and the mixed Gaussian impulsive noises are exploited to test the effectiveness of this method. The experimental results show that the proposed method outperforms the standard median filter by 1~2db in PSNR. The effect of the proposed method becomes better with the rise in noise level. In the experiments using constrained LMS optimization or genie algorithm to estimate the parameters of the filter, the proposed scheme attains 0.4~0.6db improvement in PSNR. In general, the genetic algorithm performs better than the constrained LMS by 0.1db in PSNR. Based on the experimental results, we conclude that the proposed NROM-SS filter can readily reduce the influence of the low amplitude noises. The drawback of over-correction situation, which is usually observed in the median filter, has been improved with the proposed scheme. Moreover, the two methods for optimal parameter estimation can further improve the effectiveness of the filter. Keywords- Constrained LMS；Rank order filter mean filter； |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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