A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization
A desirable photographic reproduction method should have the ability to compress high-dynamic-range images to low-dynamic-range displays that faithfully preserve all visual information. However, during the compression process, most reproduction methods face challenges in striking a balance between m...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/18/6038 |
| _version_ | 1797517286135824384 |
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| author | Yu-Hsiu Lin Kai-Lung Hua Yung-Yao Chen I-Ying Chen Yun-Chen Tsai |
| author_facet | Yu-Hsiu Lin Kai-Lung Hua Yung-Yao Chen I-Ying Chen Yun-Chen Tsai |
| author_sort | Yu-Hsiu Lin |
| collection | DOAJ |
| description | A desirable photographic reproduction method should have the ability to compress high-dynamic-range images to low-dynamic-range displays that faithfully preserve all visual information. However, during the compression process, most reproduction methods face challenges in striking a balance between maintaining global contrast and retaining majority of local details in a real-world scene. To address this problem, this study proposes a new photographic reproduction method that can smoothly take global and local features into account. First, a highlight/shadow region detection scheme is used to obtain prior information to generate a weight map. Second, a mutually hybrid histogram analysis is performed to extract global/local features in parallel. Third, we propose a feature fusion scheme to construct the virtual combined histogram, which is achieved by adaptively fusing global/local features through the use of Gaussian mixtures according to the weight map. Finally, the virtual combined histogram is used to formulate the pixel-wise mapping function. As both global and local features are simultaneously considered, the output image has a natural and visually pleasing appearance. The experimental results demonstrated the effectiveness of the proposed method and the superiority over other seven state-of-the-art methods. |
| first_indexed | 2024-03-10T07:14:35Z |
| format | Article |
| id | doaj.art-8dbd855cf8354dcaab27c9cc869838de |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T07:14:35Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8dbd855cf8354dcaab27c9cc869838de2023-11-22T15:10:39ZengMDPI AGSensors1424-82202021-09-012118603810.3390/s21186038A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram EqualizationYu-Hsiu Lin0Kai-Lung Hua1Yung-Yao Chen2I-Ying Chen3Yun-Chen Tsai4Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106, TaiwanDepartment of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei 106, TaiwanDepartment of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei 106, TaiwanGraduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106, TaiwanGraduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106, TaiwanA desirable photographic reproduction method should have the ability to compress high-dynamic-range images to low-dynamic-range displays that faithfully preserve all visual information. However, during the compression process, most reproduction methods face challenges in striking a balance between maintaining global contrast and retaining majority of local details in a real-world scene. To address this problem, this study proposes a new photographic reproduction method that can smoothly take global and local features into account. First, a highlight/shadow region detection scheme is used to obtain prior information to generate a weight map. Second, a mutually hybrid histogram analysis is performed to extract global/local features in parallel. Third, we propose a feature fusion scheme to construct the virtual combined histogram, which is achieved by adaptively fusing global/local features through the use of Gaussian mixtures according to the weight map. Finally, the virtual combined histogram is used to formulate the pixel-wise mapping function. As both global and local features are simultaneously considered, the output image has a natural and visually pleasing appearance. The experimental results demonstrated the effectiveness of the proposed method and the superiority over other seven state-of-the-art methods.https://www.mdpi.com/1424-8220/21/18/6038photographic reproductionvision sensing techniquefeature fusionhuman visual systemvirtual combined histogramhistogram equalization |
| spellingShingle | Yu-Hsiu Lin Kai-Lung Hua Yung-Yao Chen I-Ying Chen Yun-Chen Tsai A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization Sensors photographic reproduction vision sensing technique feature fusion human visual system virtual combined histogram histogram equalization |
| title | A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization |
| title_full | A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization |
| title_fullStr | A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization |
| title_full_unstemmed | A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization |
| title_short | A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization |
| title_sort | new photographic reproduction method based on feature fusion and virtual combined histogram equalization |
| topic | photographic reproduction vision sensing technique feature fusion human visual system virtual combined histogram histogram equalization |
| url | https://www.mdpi.com/1424-8220/21/18/6038 |
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