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We propose a diffuser-based lensless underwater optical signal detection system. The system consists of a lensless one-dimensional (1D) camera array equipped with random phase modulators for signal acquisition and one-dimensional integral imaging convolutional neural network (1DInImCNN) for signal classification. During the acquisition process, the encoded signal transmitted by a light-emitting diode passes through a turbid medium as well as partial occlusion. The 1D diffuser-based lensless camera array is used to capture the transmitted information. The captured pseudorandom patterns are then classified through the 1DInImCNN to output the desired signal. We compared our proposed underwater lensless optical signal detection system with an equivalent lens-based underwater optical signal detection system in terms of detection performance and computational cost. The results show that the former outperforms the latter. Moreover, we use dimensionality reduction on the lensless pattern and study their theoretical computational costs and detection performance. The results show that the detection performance of lensless systems does not suffer appreciably. This makes lensless systems a great candidate for low-cost compressive underwater optical imaging and signal detection.
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Recent advances in lensless imaging
Lensless imaging provides opportunities to design imaging systems free from the constraints imposed by traditional camera architectures. Due to advances in imaging hardware, fabrication techniques, and new algorithms, researchers have recently developed lensless imaging systems that are extremely compact and lightweight or able to image higher-dimensional quantities. Here we review these recent advances and describe the design principles and their effects that one should consider when developing and using lensless imaging systems.
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- Award ID(s):
- 1652633
- PAR ID:
- 10369336
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Optica
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2334-2536
- Format(s):
- Medium: X Size: Article No. 1
- Size(s):
- Article No. 1
- Sponsoring Org:
- National Science Foundation
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