Back to Search
Start Over
Compact biologically inspired camera with computational compound eye
- Source :
- Nanophotonics, Vol 13, Iss 16, Pp 2879-2890 (2024)
- Publication Year :
- 2024
- Publisher :
- De Gruyter, 2024.
-
Abstract
- The growing interests have been witnessed in the evolution and improvement of artificial compound eyes (CE) inspired by arthropods. However, the existing CE cameras are suffering from a defocusing problem due to the incompatibility with commercial CMOS cameras. Inspired by the CEs of South American Shrimps, we report a compact biologically inspired camera that enables wide-field-of-view (FOV), high-resolution imaging and sensitive 3D moving trajectory reconstruction. To overcome the defocusing problem, a deep learning architecture with distance regulation is proposed to achieve wide-range-clear imaging, without any hardware or complex front-end design, which greatly reduces system complexity and size. The architecture is composed of a variant of Unet and Pyramid-multi-scale attention, with designed short, middle and long distance regulation. Compared to the current competitive well-known models, our method is at least 2 dB ahead. Here we describe the high-resolution computational-CE camera with 271 ommatidia, with a weight of 5.4 g an area of 3 × 3 cm2 and 5-mm thickness, which achieves compatibility and integration of CE with commercial CMOS. The experimental result illustrates this computational-CE camera has competitive advantages in enhanced resolution and sensitive 3D live moving trajectory reconstruction. The compact camera has promising applications in nano-optics fields such as medical endoscopy, panoramic imaging and vision robotics.
- Subjects :
- compound eye
imaging system
deep learning
integrated optics
Physics
QC1-999
Subjects
Details
- Language :
- English
- ISSN :
- 21928614
- Volume :
- 13
- Issue :
- 16
- Database :
- Directory of Open Access Journals
- Journal :
- Nanophotonics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.ba3155dbc727449db303a4992b8bb060
- Document Type :
- article
- Full Text :
- https://doi.org/10.1515/nanoph-2023-0782