Single Image Dehazing Using Global Illumination Compensation
The existing dehazing algorithms hardly consider background interference in the process of estimating the atmospheric illumination value and transmittance, resulting in an unsatisfactory dehazing effect. In order to solve the problem, this paper proposes a novel global illumination compensation-base...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/11/4169 |
| _version_ | 1797491614663311360 |
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| author | Junbao Zheng Chenke Xu Wei Zhang Xu Yang |
| author_facet | Junbao Zheng Chenke Xu Wei Zhang Xu Yang |
| author_sort | Junbao Zheng |
| collection | DOAJ |
| description | The existing dehazing algorithms hardly consider background interference in the process of estimating the atmospheric illumination value and transmittance, resulting in an unsatisfactory dehazing effect. In order to solve the problem, this paper proposes a novel global illumination compensation-based image-dehazing algorithm (GIC). The GIC method compensates for the intensity of light scattered when light passes through atmospheric particles such as fog. Firstly, the illumination compensation was accomplished in the CIELab color space using the shading partition enhancement mechanism. Secondly, the atmospheric illumination values and transmittance parameters of these enhanced images were computed to improve the performance of atmospheric-scattering models, in order to reduce the interference of background signals. Eventually, the dehazing result maps with reduced background interference were obtained with the computed atmospheric-scattering model. The dehazing experiments were carried out on the public data set, and the dehazing results of the foggy image were compared with cutting-edge dehazing algorithms. The experimental results illustrate that the proposed GIC algorithm shows enhanced consistency with the real-imaging situation in estimating atmospheric illumination and transmittance. Compared with established image-dehazing methods, the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) metrics of the proposed GIC method increased by 3.25 and 0.084, respectively. |
| first_indexed | 2024-03-10T00:51:50Z |
| format | Article |
| id | doaj.art-621ef165d27e440185f59d1a578d5fc8 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T00:51:50Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-621ef165d27e440185f59d1a578d5fc82023-11-23T14:49:43ZengMDPI AGSensors1424-82202022-05-012211416910.3390/s22114169Single Image Dehazing Using Global Illumination CompensationJunbao Zheng0Chenke Xu1Wei Zhang2Xu Yang3School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, ChinaSchool of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, ChinaSchool of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, ChinaSchool of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, ChinaThe existing dehazing algorithms hardly consider background interference in the process of estimating the atmospheric illumination value and transmittance, resulting in an unsatisfactory dehazing effect. In order to solve the problem, this paper proposes a novel global illumination compensation-based image-dehazing algorithm (GIC). The GIC method compensates for the intensity of light scattered when light passes through atmospheric particles such as fog. Firstly, the illumination compensation was accomplished in the CIELab color space using the shading partition enhancement mechanism. Secondly, the atmospheric illumination values and transmittance parameters of these enhanced images were computed to improve the performance of atmospheric-scattering models, in order to reduce the interference of background signals. Eventually, the dehazing result maps with reduced background interference were obtained with the computed atmospheric-scattering model. The dehazing experiments were carried out on the public data set, and the dehazing results of the foggy image were compared with cutting-edge dehazing algorithms. The experimental results illustrate that the proposed GIC algorithm shows enhanced consistency with the real-imaging situation in estimating atmospheric illumination and transmittance. Compared with established image-dehazing methods, the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) metrics of the proposed GIC method increased by 3.25 and 0.084, respectively.https://www.mdpi.com/1424-8220/22/11/4169fog imagingimage dehazingshading partition enhancement mechanismglobal illumination compensation factordark channel prior (DCP)guided filtering |
| spellingShingle | Junbao Zheng Chenke Xu Wei Zhang Xu Yang Single Image Dehazing Using Global Illumination Compensation Sensors fog imaging image dehazing shading partition enhancement mechanism global illumination compensation factor dark channel prior (DCP) guided filtering |
| title | Single Image Dehazing Using Global Illumination Compensation |
| title_full | Single Image Dehazing Using Global Illumination Compensation |
| title_fullStr | Single Image Dehazing Using Global Illumination Compensation |
| title_full_unstemmed | Single Image Dehazing Using Global Illumination Compensation |
| title_short | Single Image Dehazing Using Global Illumination Compensation |
| title_sort | single image dehazing using global illumination compensation |
| topic | fog imaging image dehazing shading partition enhancement mechanism global illumination compensation factor dark channel prior (DCP) guided filtering |
| url | https://www.mdpi.com/1424-8220/22/11/4169 |
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