High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise
Multiple line characterization is a most common issue in image processing. A specific formalism turns the contour detection issue of image processing into a source localization issue of array processing. However, the existing methods do not address correlated noise. As a result, the detection perfor...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2010-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2010/630768 |
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| _version_ | 1849400374905012224 |
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| author | Haiping Jiang Salah Bourennane Caroline Fossati |
| author_facet | Haiping Jiang Salah Bourennane Caroline Fossati |
| author_sort | Haiping Jiang |
| collection | DOAJ |
| description | Multiple line characterization is a most common issue in image processing. A specific formalism turns the contour detection issue of image processing into a source localization issue of array processing. However, the existing methods do not address correlated noise. As a result, the detection performance is degraded. In this paper, we propose to improve the subspace-based high-resolution methods by computing the fourth-order slice cumulant matrix of the received signals instead of second-order statistics, and we estimate contour parameters out of images impaired with correlated Gaussian noise. Simulation results are presented and show that the proposed methods improve line characterization performance compared to second-order statistics. |
| format | Article |
| id | doaj-art-88bbb213e2894b66aac6aa1ef1bf2277 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2010-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-88bbb213e2894b66aac6aa1ef1bf22772025-08-20T03:38:05ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552010-01-01201010.1155/2010/630768630768High-Resolution Algorithm for Image Segmentation in the Presence of Correlated NoiseHaiping Jiang0Salah Bourennane1Caroline Fossati2Institut Fresnel/UMR CNRS 6133, Ecole Centrale Marseille, D.U. de Saint-Jérôme, 13397 Marseille Cédex 20, FranceInstitut Fresnel/UMR CNRS 6133, Ecole Centrale Marseille, D.U. de Saint-Jérôme, 13397 Marseille Cédex 20, FranceInstitut Fresnel/UMR CNRS 6133, Ecole Centrale Marseille, D.U. de Saint-Jérôme, 13397 Marseille Cédex 20, FranceMultiple line characterization is a most common issue in image processing. A specific formalism turns the contour detection issue of image processing into a source localization issue of array processing. However, the existing methods do not address correlated noise. As a result, the detection performance is degraded. In this paper, we propose to improve the subspace-based high-resolution methods by computing the fourth-order slice cumulant matrix of the received signals instead of second-order statistics, and we estimate contour parameters out of images impaired with correlated Gaussian noise. Simulation results are presented and show that the proposed methods improve line characterization performance compared to second-order statistics.http://dx.doi.org/10.1155/2010/630768 |
| spellingShingle | Haiping Jiang Salah Bourennane Caroline Fossati High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise Journal of Electrical and Computer Engineering |
| title | High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise |
| title_full | High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise |
| title_fullStr | High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise |
| title_full_unstemmed | High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise |
| title_short | High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise |
| title_sort | high resolution algorithm for image segmentation in the presence of correlated noise |
| url | http://dx.doi.org/10.1155/2010/630768 |
| work_keys_str_mv | AT haipingjiang highresolutionalgorithmforimagesegmentationinthepresenceofcorrelatednoise AT salahbourennane highresolutionalgorithmforimagesegmentationinthepresenceofcorrelatednoise AT carolinefossati highresolutionalgorithmforimagesegmentationinthepresenceofcorrelatednoise |