SeaScan: An Energy-Efficient Underwater Camera for Wireless 3D Color Imaging
We present the design, implementation, and evaluation of SeaScan, an energy-efficient camera for 3D imaging of underwater environments. At the core of SeaScan's design is a trinocular lensing system, which employs three ultra-low-power monochromatic image sensors to reconstruct color images. Each of the sensors is equipped with a different filter (red, green, and blue) for color capture. The design introduces multiple innovations to enable reconstructing 3D color images from the captured monochromatic ones. This includes an ML-based cross-color alignment architecture to combine the monochromatic images. It also includes a cross-refractive compensation technique that overcomes the distortion of the wide-angle imaging of the low-power CMOS sensors in underwater environments. We built an end-to-end prototype of SeaScan, including color filter integration, 3D reconstruction, compression, and underwater backscatter communication. Our evaluation in real-world underwater environments demonstrates that SeaScan can capture underwater color images with as little as 23.6 mJ, which represents 37X reduction in energy consumption in comparison to the lowest-energy state-of-the-art underwater imaging system. We also report qualitative and quantitative evaluation of SeaScan's color reconstruction and demonstrate its success in comparison to multiple potential alternative techniques (both geometric and ML-based) in the literature. SeaScan's ability to image underwater environments at such low energy opens up important applications in long-term monitoring for ocean climate change, seafood production, and scientific discovery.
Authors
- Jack Rademacher (ORCID: https://orcid.org/0000-0002-3325-4352)
- Tara Boroushaki (ORCID: https://orcid.org/0000-0002-3829-648X)
- Ritik Patnaik (ORCID: https://orcid.org/0000-0002-6136-8859)
- Nazish Naeem (ORCID: https://orcid.org/0000-0001-8725-1619)
- Fadel Adib (ORCID: https://orcid.org/0000-0003-2593-2069)
Institutions
- Massachusetts Institute of Technology (US)
Publication Details
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1145/3636534.3690661
- Citations
- 3
- Primary Topic
- Image Enhancement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.75
Funders
- National Science Foundation
- Office of Naval Research