Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm
Single image dehazing remains a seminal area of study in computer vision. Despite the huge number of studies that have addressed haze in a single image, the restoration images have not yet reached a satisfactory level in terms of visual appearance and time complexity burden. In this paper, a novel s...
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| Format: | Article |
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Springer
2018
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| _version_ | 1796979652652171264 |
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| author | Khmag, Asem Sy Mohamed, Sy Abd Rahman Al-haddad Ramli, Abd Rahman Kalantar, Bahareh |
| author_facet | Khmag, Asem Sy Mohamed, Sy Abd Rahman Al-haddad Ramli, Abd Rahman Kalantar, Bahareh |
| author_sort | Khmag, Asem |
| collection | UPM |
| description | Single image dehazing remains a seminal area of study in computer vision. Despite the huge number of studies that have addressed haze in a single image, the restoration images have not yet reached a satisfactory level in terms of visual appearance and time complexity burden. In this paper, a novel single image haze removal technique based on edge and fine texture preserving is introduced. To achieve better visual quality from the hazy image, the proposed technique uses mean vector L2-norm that is core of window sampling to estimate the transmission map. Then, second-generation wavelet transform filter is utilized in order to enhance the estimated transmission map of the resulted image. The usage of second-generation wavelet filter in this paper is due to its effectiveness while achieving fast speed. Experimental outcomes present that the proposed technique achieves competitive achievements in comparison with up-to-date state-of-the-art image dehazing methods in both quantitative and qualitative assessments, i.e., visual effects, universality, and computational processing speed. |
| first_indexed | 2024-03-06T10:12:04Z |
| format | Article |
| id | upm.eprints-73899 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T10:12:04Z |
| publishDate | 2018 |
| publisher | Springer |
| record_format | dspace |
| spelling | upm.eprints-738992022-11-23T03:31:42Z http://psasir.upm.edu.my/id/eprint/73899/ Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm Khmag, Asem Sy Mohamed, Sy Abd Rahman Al-haddad Ramli, Abd Rahman Kalantar, Bahareh Single image dehazing remains a seminal area of study in computer vision. Despite the huge number of studies that have addressed haze in a single image, the restoration images have not yet reached a satisfactory level in terms of visual appearance and time complexity burden. In this paper, a novel single image haze removal technique based on edge and fine texture preserving is introduced. To achieve better visual quality from the hazy image, the proposed technique uses mean vector L2-norm that is core of window sampling to estimate the transmission map. Then, second-generation wavelet transform filter is utilized in order to enhance the estimated transmission map of the resulted image. The usage of second-generation wavelet filter in this paper is due to its effectiveness while achieving fast speed. Experimental outcomes present that the proposed technique achieves competitive achievements in comparison with up-to-date state-of-the-art image dehazing methods in both quantitative and qualitative assessments, i.e., visual effects, universality, and computational processing speed. Springer 2018-05 Article PeerReviewed Khmag, Asem and Sy Mohamed, Sy Abd Rahman Al-haddad and Ramli, Abd Rahman and Kalantar, Bahareh (2018) Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm. The Visual Computer volume, 34 (5). 675 - 688. ISSN 0178-2789; ESSN: 1432-2315 https://link.springer.com/article/10.1007/s00371-017-1406-5 10.1007/s00371-017-1406-5 |
| spellingShingle | Khmag, Asem Sy Mohamed, Sy Abd Rahman Al-haddad Ramli, Abd Rahman Kalantar, Bahareh Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm |
| title | Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm |
| title_full | Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm |
| title_fullStr | Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm |
| title_full_unstemmed | Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm |
| title_short | Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm |
| title_sort | single image dehazing using second generation wavelet transforms and the mean vector l2 norm |
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