Light Field Spatial Resolution Enhancement Framework
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911866899398656 |
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| author | Shabbir, Javeria Alam, Muhammad Zeshan. Mukati, M. Umair |
| author_facet | Shabbir, Javeria Alam, Muhammad Zeshan. Mukati, M. Umair |
| contents | Light field (LF) imaging captures both angular and spatial light distributions, enabling advanced photographic techniques. However, micro-lens array (MLA)- based cameras face a spatial-angular resolution tradeoff due to a single shared sensor. We propose a novel light field framework for resolution enhancement, employing a modular approach. The first module generates a high-resolution, all-in-focus image. The second module, a texture transformer network, enhances the resolution of each light field perspective independently using the output of the first module as a reference image. The final module leverages light field regularity to jointly improve resolution across all LF image perspectives. Our approach demonstrates superior performance to existing methods in both qualitative and quantitative evaluations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_02787 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Light Field Spatial Resolution Enhancement Framework Shabbir, Javeria Alam, Muhammad Zeshan. Mukati, M. Umair Computer Vision and Pattern Recognition Light field (LF) imaging captures both angular and spatial light distributions, enabling advanced photographic techniques. However, micro-lens array (MLA)- based cameras face a spatial-angular resolution tradeoff due to a single shared sensor. We propose a novel light field framework for resolution enhancement, employing a modular approach. The first module generates a high-resolution, all-in-focus image. The second module, a texture transformer network, enhances the resolution of each light field perspective independently using the output of the first module as a reference image. The final module leverages light field regularity to jointly improve resolution across all LF image perspectives. Our approach demonstrates superior performance to existing methods in both qualitative and quantitative evaluations. |
| title | Light Field Spatial Resolution Enhancement Framework |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2405.02787 |