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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2407.01789 |
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| _version_ | 1866916308964081664 |
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| author | Karaoglu, Ali |
| author_facet | Karaoglu, Ali |
| contents | In contemporary imaging systems, achieving optimal auto-focus (AF) performance hinges on precise lens positioning. Extensive research has delved into refining algorithms for determining the ideal lens position across passive, active, and hybrid autofocus systems. This paper explores the mathematical intricacies and practical considerations essential for optimizing lens positions during focus searches, addressing overarching challenges encountered in AF systems, such as balancing speed and accuracy. Moreover, the lens position calculations proposed herein can be applied to various focus algorithms, including focus bracketing. The proposed method offers adaptability and scalability, rendering it suitable for integration into a wide array of camera systems, ranging from smartphones and DSLRs to microscopes and industrial imaging devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_01789 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimal Sample Lens Positioning in Digital Camera Systems Karaoglu, Ali Computer Vision and Pattern Recognition Image and Video Processing In contemporary imaging systems, achieving optimal auto-focus (AF) performance hinges on precise lens positioning. Extensive research has delved into refining algorithms for determining the ideal lens position across passive, active, and hybrid autofocus systems. This paper explores the mathematical intricacies and practical considerations essential for optimizing lens positions during focus searches, addressing overarching challenges encountered in AF systems, such as balancing speed and accuracy. Moreover, the lens position calculations proposed herein can be applied to various focus algorithms, including focus bracketing. The proposed method offers adaptability and scalability, rendering it suitable for integration into a wide array of camera systems, ranging from smartphones and DSLRs to microscopes and industrial imaging devices. |
| title | Optimal Sample Lens Positioning in Digital Camera Systems |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2407.01789 |