Soft morphological filter optimization using a genetic algorithm for noise elimination
Digital image quality is of importance in almost all image processing applications. Many different approaches have been proposed for restoring the image quality depending on the nature of the degradation. One of the most common problems that cause such degradation is impulse noise. In general, well...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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2014
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| Online Access: | https://eprints.nottingham.ac.uk/28548/ |
| _version_ | 1848793592763514880 |
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| author | Ercal, Turker Özcan, Ender Asta, Shahriar |
| author_facet | Ercal, Turker Özcan, Ender Asta, Shahriar |
| author_sort | Ercal, Turker |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Digital image quality is of importance in almost all image processing applications. Many different approaches have been proposed for restoring the image quality depending on the nature of the degradation. One of the most common problems that cause such degradation is impulse noise. In general, well known median filters are preferred for eliminating different types of noise. Soft morphological filters are recently introduced and have been in use for many purposes. In this study, we present a Genetic Algorithm (GA) which combines different objectives as a weighted sum under a single evaluation function and generates a soft morphological filter to deal with impulse noise, after a training process with small images. The automatically generated filter performs better than the median filter and achieves comparable results to the best known filters from the literature over a set of benchmark instances that are larger than the training instances. Moreover, although the training process involves only impulse noise added images, the same evolved filter performs better than the median filter for eliminating Gaussian noise as well. |
| first_indexed | 2025-11-14T19:02:45Z |
| format | Conference or Workshop Item |
| id | nottingham-28548 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:02:45Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-285482020-05-04T20:16:30Z https://eprints.nottingham.ac.uk/28548/ Soft morphological filter optimization using a genetic algorithm for noise elimination Ercal, Turker Özcan, Ender Asta, Shahriar Digital image quality is of importance in almost all image processing applications. Many different approaches have been proposed for restoring the image quality depending on the nature of the degradation. One of the most common problems that cause such degradation is impulse noise. In general, well known median filters are preferred for eliminating different types of noise. Soft morphological filters are recently introduced and have been in use for many purposes. In this study, we present a Genetic Algorithm (GA) which combines different objectives as a weighted sum under a single evaluation function and generates a soft morphological filter to deal with impulse noise, after a training process with small images. The automatically generated filter performs better than the median filter and achieves comparable results to the best known filters from the literature over a set of benchmark instances that are larger than the training instances. Moreover, although the training process involves only impulse noise added images, the same evolved filter performs better than the median filter for eliminating Gaussian noise as well. 2014 Conference or Workshop Item PeerReviewed Ercal, Turker, Özcan, Ender and Asta, Shahriar (2014) Soft morphological filter optimization using a genetic algorithm for noise elimination. In: UK Workshop on Computational Intelligence (UKCI2014), 8-10 Sept 2014, Bradford, UK. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6930177 |
| spellingShingle | Ercal, Turker Özcan, Ender Asta, Shahriar Soft morphological filter optimization using a genetic algorithm for noise elimination |
| title | Soft morphological filter optimization using a genetic algorithm for noise elimination |
| title_full | Soft morphological filter optimization using a genetic algorithm for noise elimination |
| title_fullStr | Soft morphological filter optimization using a genetic algorithm for noise elimination |
| title_full_unstemmed | Soft morphological filter optimization using a genetic algorithm for noise elimination |
| title_short | Soft morphological filter optimization using a genetic algorithm for noise elimination |
| title_sort | soft morphological filter optimization using a genetic algorithm for noise elimination |
| url | https://eprints.nottingham.ac.uk/28548/ https://eprints.nottingham.ac.uk/28548/ |