Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach
Computer vision requires high-quality input images to facilitate image interpretation and analysis tasks. However, the image acquisition process does not always produce good-quality images. In outdoor environments, image quality is determined by weather or environmental conditions. Bad weather condi...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-12-01
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| Series: | Cybernetics and Information Technologies |
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| Online Access: | https://doi.org/10.2478/cait-2024-0039 |
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| author | Rahmawati Lailia Rustad Supriadi Marjuni Aris Soeleman Mochammad Arief Supriyanto Catur Shidik Guruh Fajar |
| author_facet | Rahmawati Lailia Rustad Supriadi Marjuni Aris Soeleman Mochammad Arief Supriyanto Catur Shidik Guruh Fajar |
| author_sort | Rahmawati Lailia |
| collection | DOAJ |
| description | Computer vision requires high-quality input images to facilitate image interpretation and analysis tasks. However, the image acquisition process does not always produce good-quality images. In outdoor environments, image quality is determined by weather or environmental conditions. Bad weather conditions due to pollution particles in the atmosphere such as smoke, fog, and haze can degrade image quality, such as contrast, brightness, and sharpness. This research proposes to obtain a better haze-free image from a hazy image by utilizing the Laplacian filtering and image enhancement techniques in the transmission map reconstruction based on the dark channel prior approach. Experimental results show that the proposed method could improve the visual quality of the dehazed images from 45% to 56% compared to the ground-truth images. The proposed method is also fairly competitive compared to similar methods in the same domain. |
| format | Article |
| id | doaj-art-2e7e7e3a978041af8ac6fe8f28e6a89c |
| institution | OA Journals |
| issn | 1314-4081 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Cybernetics and Information Technologies |
| spelling | doaj-art-2e7e7e3a978041af8ac6fe8f28e6a89c2025-08-20T01:47:45ZengSciendoCybernetics and Information Technologies1314-40812024-12-0124412614210.2478/cait-2024-0039Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior ApproachRahmawati Lailia0Rustad Supriadi1Marjuni Aris2Soeleman Mochammad Arief3Supriyanto Catur4Shidik Guruh Fajar5Department of Informatics Engineering, Universitas Dian Nuswantoro, Semarang, IndonesiaDepartment of Informatics Engineering, Universitas Dian Nuswantoro, Semarang, IndonesiaDepartment of Informatics Engineering, Universitas Dian Nuswantoro, Semarang, IndonesiaDepartment of Informatics Engineering, Universitas Dian Nuswantoro, Semarang, IndonesiaDepartment of Informatics Engineering, Universitas Dian Nuswantoro, Semarang, IndonesiaDepartment of Informatics Engineering, Universitas Dian Nuswantoro, Semarang, IndonesiaComputer vision requires high-quality input images to facilitate image interpretation and analysis tasks. However, the image acquisition process does not always produce good-quality images. In outdoor environments, image quality is determined by weather or environmental conditions. Bad weather conditions due to pollution particles in the atmosphere such as smoke, fog, and haze can degrade image quality, such as contrast, brightness, and sharpness. This research proposes to obtain a better haze-free image from a hazy image by utilizing the Laplacian filtering and image enhancement techniques in the transmission map reconstruction based on the dark channel prior approach. Experimental results show that the proposed method could improve the visual quality of the dehazed images from 45% to 56% compared to the ground-truth images. The proposed method is also fairly competitive compared to similar methods in the same domain.https://doi.org/10.2478/cait-2024-0039dehazed imagesingle image dehazingdark channel priortransmission maplaplacian transform. |
| spellingShingle | Rahmawati Lailia Rustad Supriadi Marjuni Aris Soeleman Mochammad Arief Supriyanto Catur Shidik Guruh Fajar Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach Cybernetics and Information Technologies dehazed image single image dehazing dark channel prior transmission map laplacian transform. |
| title | Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach |
| title_full | Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach |
| title_fullStr | Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach |
| title_full_unstemmed | Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach |
| title_short | Transmission Map Refinement Using Laplacian Transform on Single Image Dehazing Based on Dark Channel Prior Approach |
| title_sort | transmission map refinement using laplacian transform on single image dehazing based on dark channel prior approach |
| topic | dehazed image single image dehazing dark channel prior transmission map laplacian transform. |
| url | https://doi.org/10.2478/cait-2024-0039 |
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