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Rapid advancements in autonomous systems and the Internet of Things have necessitated the development of compact and low-power image sensors to bridge the gap between the digital and physical world. To that end, sub-wavelength diffractive optics, commonly known as meta-optics, have garnered significant interest from the optics and photonics community due to their ability to achieve multiple functionalities within a small form factor. Despite years of research, however, the performance of meta-optics has often remained inferior compared to that of traditional refractive optics. In parallel, computational imaging techniques have emerged as a promising path to miniaturize optical systems, albeit often at the expense of higher power and latency. The lack of desired performance from either meta-optical or computational solutions has motivated researchers to look into a jointly optimized meta-optical–digital solution. While the meta-optical front end can preprocess the scene to reduce the computational load on the digital back end, the computational back end can in turn relax requirements on the meta-optics. In this Perspective, we provide an overview of this up-and-coming field, termed here as “software-defined meta-optics.” We highlight recent contributions that have advanced the current state of the art and point out directions toward which future research efforts should be directed to leverage the full potential of subwavelength photonic platforms in imaging and sensing applications. Synergistic technology transfer and commercialization of meta-optic technologies will pave the way for highly efficient, compact, and low-power imaging systems of the future.
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Computational imaging with meta-optics
Sub-wavelength diffractive meta-optics have emerged as a versatile platform to manipulate light fields at will, due to their ultra-small form factor and flexible multifunctionalities. However, miniaturization and multimodality are typically compromised by a reduction in imaging performance; thus, meta-optics often yield lower resolution and stronger aberration compared to traditional refractive optics. Concurrently, computational approaches have become popular to improve the image quality of traditional cameras and exceed limitations posed by refractive lenses. This in turn often comes at the expense of higher power and latency, and such systems are typically limited by the availability of certain refractive optics. Limitations in both fields have thus sparked cross-disciplinary efforts to not only overcome these roadblocks but also to go beyond and provide synergistic meta-optical–digital solutions that surpass the potential of the individual components. For instance, an application-specific meta-optical frontend can preprocess the light field of a scene and focus it onto the sensor with a desired encoding, which can either ease the computational load on the digital backend or can intentionally alleviate certain meta-optical aberrations. In this review, we introduce the fundamentals, summarize the development of meta-optical computational imaging, focus on latest advancements that redefine the current state of the art, and give a perspective on research directions that leverage the full potential of sub-wavelength photonic platforms in imaging and sensing applications. The current advancement of meta-optics and recent investments by foundries and technology partners have the potential to provide synergistic future solutions for highly efficient, compact, and low-power imaging systems.
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- Award ID(s):
- 2127235
- PAR ID:
- 10608429
- Publisher / Repository:
- Optica Publishing Group
- Date Published:
- Journal Name:
- Optica
- Volume:
- 12
- Issue:
- 6
- ISSN:
- 2334-2536
- Page Range / eLocation ID:
- 774
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1364/OPTICA.546382
