Multiple-Particle Autofocusing Algorithm Using Axial Resolution and Morphological Analyses Based on Digital Holography
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910889936945152 |
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| author | Li, Wei-Na Zhou, Yi Chen, Jiatai Ou, Hongjie Xie, XiangSheng |
| author_facet | Li, Wei-Na Zhou, Yi Chen, Jiatai Ou, Hongjie Xie, XiangSheng |
| contents | We propose an autofocusing algorithm to obtain, relatively accurately, the 3D position of each particle, particularly its axial location, and particle number of a dense transparent particle solution via its hologram. First, morphological analyses and constrained intensity are used on raw reconstructed images to obtain information on candidate focused particles. Second, axial resolution is used to obtain the real focused particles. Based on the mean intensity and equivalent diameter of each candidate focused particle, all focused particles are eventually secured. Our proposed method can rapidly provide relatively accurate ground-truth axial positions to solve the autofocusing problem that occurs with dense particles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_18038 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multiple-Particle Autofocusing Algorithm Using Axial Resolution and Morphological Analyses Based on Digital Holography Li, Wei-Na Zhou, Yi Chen, Jiatai Ou, Hongjie Xie, XiangSheng Signal Processing Computer Vision and Pattern Recognition Image and Video Processing We propose an autofocusing algorithm to obtain, relatively accurately, the 3D position of each particle, particularly its axial location, and particle number of a dense transparent particle solution via its hologram. First, morphological analyses and constrained intensity are used on raw reconstructed images to obtain information on candidate focused particles. Second, axial resolution is used to obtain the real focused particles. Based on the mean intensity and equivalent diameter of each candidate focused particle, all focused particles are eventually secured. Our proposed method can rapidly provide relatively accurate ground-truth axial positions to solve the autofocusing problem that occurs with dense particles. |
| title | Multiple-Particle Autofocusing Algorithm Using Axial Resolution and Morphological Analyses Based on Digital Holography |
| topic | Signal Processing Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2503.18038 |