IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION
When remote sensing photos are taken, they are often captured in hazy circumstances such as fog, snow, thin clouds, dust, and other similar situations, which causes the contrast in the image to decrease. The term "dehazing" refers to the process of removing haze or other atmospheric pollut...
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| Format: | Article |
| Language: | English |
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University of Kragujevac
2025-03-01
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| Series: | Proceedings on Engineering Sciences |
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| Online Access: | https://pesjournal.net/journal/v7-n1/50.pdf |
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| author | Bhaskar Reddy Bada Mahaboob Basha S Imran Khan Patan Eramma Boda |
| author_facet | Bhaskar Reddy Bada Mahaboob Basha S Imran Khan Patan Eramma Boda |
| author_sort | Bhaskar Reddy Bada |
| collection | DOAJ |
| description | When remote sensing photos are taken, they are often captured in hazy circumstances such as fog, snow, thin clouds, dust, and other similar situations, which causes the contrast in the image to decrease. The term "dehazing" refers to the process of removing haze or other atmospheric pollutants from a photograph. The goal of this approach is to improve the overall quality of the image and to make it more appealing to the customer. However, the majority of the procedures that are considered to be state of the art were not successful in completely removing the atmospheric effects from the picture. This article is primarily focused on the construction of a gray world optimization (GWO) algorithm for the purpose of providing an accurate assessment of ambient light. This is done in order to find a solution to the issue. A unique approach for dark channel prior-based transmission map estimation and refining is also developed as part of this study. This method is applied in a pixel-wise and patch-wise way. Because of this, the atmospheric effects are resolved in each and every patch that is based on pixels. In conclusion, a rapid iterative domain guided image filtering (ID-GIF) technique was created in order to achieve the goal of obtaining smoother output with dehazing qualities. Compared to the methodologies that are considered to be state of the art, the findings of the simulation demonstrate that the work that is being suggested offers superior quantitative and qualitative outcomes. |
| format | Article |
| id | doaj-art-052956a2f4d84d08b6e11332a813fab9 |
| institution | OA Journals |
| issn | 2620-2832 2683-4111 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | University of Kragujevac |
| record_format | Article |
| series | Proceedings on Engineering Sciences |
| spelling | doaj-art-052956a2f4d84d08b6e11332a813fab92025-08-20T01:57:35ZengUniversity of KragujevacProceedings on Engineering Sciences2620-28322683-41112025-03-017147348410.24874/PES07.01D.004IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATIONBhaskar Reddy Bada 0https://orcid.org/0000-0002-3200-0182Mahaboob Basha S 1https://orcid.org/0009-0003-2565-2427Imran Khan Patan 2https://orcid.org/0009-0000-2270-4373Eramma Boda 3https://orcid.org/0009-0001-0741-7584Department of Electronics and Communication Engineering, St. Peters Engineering College, Telangana500100, India. Department of Electronics and Communication Engineering, St. Johns College of Engineering and Technology, Yemmiganur-518360, Andhra Pradesh, India Department of Electronics and Communication Engineering, St. Johns College of Engineering and Technology, Yemmiganur-518360, Andhra Pradesh, India. Department of Electronics and Communication Engineering, G. Pullaiah College of Engineering and Technology, Kurnool-518002, Andhra Pradesh, India. When remote sensing photos are taken, they are often captured in hazy circumstances such as fog, snow, thin clouds, dust, and other similar situations, which causes the contrast in the image to decrease. The term "dehazing" refers to the process of removing haze or other atmospheric pollutants from a photograph. The goal of this approach is to improve the overall quality of the image and to make it more appealing to the customer. However, the majority of the procedures that are considered to be state of the art were not successful in completely removing the atmospheric effects from the picture. This article is primarily focused on the construction of a gray world optimization (GWO) algorithm for the purpose of providing an accurate assessment of ambient light. This is done in order to find a solution to the issue. A unique approach for dark channel prior-based transmission map estimation and refining is also developed as part of this study. This method is applied in a pixel-wise and patch-wise way. Because of this, the atmospheric effects are resolved in each and every patch that is based on pixels. In conclusion, a rapid iterative domain guided image filtering (ID-GIF) technique was created in order to achieve the goal of obtaining smoother output with dehazing qualities. Compared to the methodologies that are considered to be state of the art, the findings of the simulation demonstrate that the work that is being suggested offers superior quantitative and qualitative outcomes.https://pesjournal.net/journal/v7-n1/50.pdfdehazeoptical fusionfast iterative domain |
| spellingShingle | Bhaskar Reddy Bada Mahaboob Basha S Imran Khan Patan Eramma Boda IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION Proceedings on Engineering Sciences dehaze optical fusion fast iterative domain |
| title | IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION |
| title_full | IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION |
| title_fullStr | IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION |
| title_full_unstemmed | IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION |
| title_short | IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION |
| title_sort | image dehazing using fast iterative domain guided image filtering with gray world optimization |
| topic | dehaze optical fusion fast iterative domain |
| url | https://pesjournal.net/journal/v7-n1/50.pdf |
| work_keys_str_mv | AT bhaskarreddybada imagedehazingusingfastiterativedomainguidedimagefilteringwithgrayworldoptimization AT mahaboobbashas imagedehazingusingfastiterativedomainguidedimagefilteringwithgrayworldoptimization AT imrankhanpatan imagedehazingusingfastiterativedomainguidedimagefilteringwithgrayworldoptimization AT erammaboda imagedehazingusingfastiterativedomainguidedimagefilteringwithgrayworldoptimization |