Genetic Fuzzy Filter Based on MAD and ROAD to Remove Mixed Impulse Noise.
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| Title: | Genetic Fuzzy Filter Based on MAD and ROAD to Remove Mixed Impulse Noise. |
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| Authors: | Janah, Nur Zahrati1 nur.zahrati@gmail.com, Baharudin, Baharum2 baharbh@petronas.com.my |
| Source: | Majlesi Journal of Electrical Engineering. Jun2010, Vol. 4 Issue 2, p63-70. 8p. 1 Color Photograph, 2 Black and White Photographs, 1 Illustration, 2 Diagrams, 1 Chart, 3 Graphs. |
| Subjects: | Genetic algorithms, MAD (Computer program language), Fuzzy measure theory, Noise control, Information storage & retrieval systems, Mathematical optimization, Electronic data processing, Electrical engineering equipment, Combinatorial optimization |
| Abstract: | In this paper, we propose a genetic fuzzy image filtering based on rank-ordered absolute differences (ROAD) and median of the absolute deviations from the median (MAD). The proposed method which is consisted of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization use genetic algorithms (GA) to perform efficient and effective noise removal. Our idea is to utilize MAD and ROAD as measures of noise probability of a pixel. Fuzzy inference system is used to justify the degree of which a pixel can be categorized as noisy. Based on the fuzzy inference result, the fuzzy switching scheme that adopts median filter as the main estimator is applied to the filtering. The GA training aims to find the best parameters for the fuzzy sets in the fuzzy noise detection. Based on the experimental results, the proposed method has successfully removed mixed impulse noise in low to medium probabilities, while keeping the uncorrupted pixels less affected by the median filtering. It also surpasses the other methods, either classical or soft computing-based approaches to impulse noise removal, in MAE and PSNR evaluations. [ABSTRACT FROM AUTHOR] |
| Copyright of Majlesi Journal of Electrical Engineering is the property of OICC Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 53337537 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Genetic Fuzzy Filter Based on MAD and ROAD to Remove Mixed Impulse Noise. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Janah%2C+Nur+Zahrati%22">Janah, Nur Zahrati</searchLink><relatesTo>1</relatesTo><i> nur.zahrati@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Baharudin%2C+Baharum%22">Baharudin, Baharum</searchLink><relatesTo>2</relatesTo><i> baharbh@petronas.com.my</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Majlesi+Journal+of+Electrical+Engineering%22">Majlesi Journal of Electrical Engineering</searchLink>. Jun2010, Vol. 4 Issue 2, p63-70. 8p. 1 Color Photograph, 2 Black and White Photographs, 1 Illustration, 2 Diagrams, 1 Chart, 3 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22MAD+%28Computer+program+language%29%22">MAD (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+measure+theory%22">Fuzzy measure theory</searchLink><br /><searchLink fieldCode="DE" term="%22Noise+control%22">Noise control</searchLink><br /><searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems%22">Information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Electrical+engineering+equipment%22">Electrical engineering equipment</searchLink><br /><searchLink fieldCode="DE" term="%22Combinatorial+optimization%22">Combinatorial optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper, we propose a genetic fuzzy image filtering based on rank-ordered absolute differences (ROAD) and median of the absolute deviations from the median (MAD). The proposed method which is consisted of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization use genetic algorithms (GA) to perform efficient and effective noise removal. Our idea is to utilize MAD and ROAD as measures of noise probability of a pixel. Fuzzy inference system is used to justify the degree of which a pixel can be categorized as noisy. Based on the fuzzy inference result, the fuzzy switching scheme that adopts median filter as the main estimator is applied to the filtering. The GA training aims to find the best parameters for the fuzzy sets in the fuzzy noise detection. Based on the experimental results, the proposed method has successfully removed mixed impulse noise in low to medium probabilities, while keeping the uncorrupted pixels less affected by the median filtering. It also surpasses the other methods, either classical or soft computing-based approaches to impulse noise removal, in MAE and PSNR evaluations. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Majlesi Journal of Electrical Engineering is the property of OICC Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 63 Subjects: – SubjectFull: Genetic algorithms Type: general – SubjectFull: MAD (Computer program language) Type: general – SubjectFull: Fuzzy measure theory Type: general – SubjectFull: Noise control Type: general – SubjectFull: Information storage & retrieval systems Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Electrical engineering equipment Type: general – SubjectFull: Combinatorial optimization Type: general Titles: – TitleFull: Genetic Fuzzy Filter Based on MAD and ROAD to Remove Mixed Impulse Noise. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Janah, Nur Zahrati – PersonEntity: Name: NameFull: Baharudin, Baharum IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2010 Type: published Y: 2010 Identifiers: – Type: issn-print Value: 2345377X Numbering: – Type: volume Value: 4 – Type: issue Value: 2 Titles: – TitleFull: Majlesi Journal of Electrical Engineering Type: main |
| ResultId | 1 |
