ArticleScience advances2022
Super-resolution image display using diffractive decoders.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Snapshot 3D image projection using a diffractive decoder.Light, science & applications · 2026Article
- Super-resolution image projection over an extended depth of field using a diffractive decoder.Light, science & applications · 2026Article
- Diffractive Optical Neural Networks: Pathways Toward Intelligent and Scalable Photonic Computing.Nanophotonics (Berlin, Germany) · 2026Review
- Metaoptics merging computational optics and optical computing toward intelligent visual perception.Science advances · 2026Review
- Automated HER2 Scoring with Uncertainty Quantification Using Lensfree Holography and Deep Learning.BME frontiers · 2026Article
- BlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images.NPJ digital medicine · 2025Article
- Universal point spread function engineering for 3D optical information processing.Light, science & applications · 2025Article
- Optimizing structured surfaces for diffractive waveguides.Nature communications · 2025Article
- All-optical complex field imaging using diffractive processors.Light, science & applications · 2024Article
- Diffractive optical computing in free space.Nature communications · 2024Review
- All-optical image denoising using a diffractive visual processor.Light, science & applications · 2024Article
- From 3D to 2D and back again.Nanophotonics (Berlin, Germany) · 2023Review
- Diffractive interconnects: all-optical permutation operation using diffractive networks.Nanophotonics (Berlin, Germany) · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-resolution image projection over a large field of view (FOV) is hindered by the restricted space-bandwidth product (SBP) of wavefront modulators. We report a deep learning-enabled diffractive display based on a jointly trained pair of an electronic encoder and a diffractive decoder to synthesize/project super-resolved images using low-resolution wavefront modulators. The digital encoder rapidly preprocesses the high-resolution images so that their spatial information is encoded into low-resolution patterns, projected via a low SBP wavefront modulator. The diffractive decoder processes these low-resolution patterns using transmissive layers structured using deep learning to all-optically synthesize/project super-resolved images at its output FOV. This diffractive image display can achieve a super-resolution factor of ~4, increasing the SBP by ~16-fold. We experimentally validate its success using 3D-printed diffractive decoders that operate at the terahertz spectrum. This diffractive image decoder can be scaled to operate at visible wavelengths and used to design large SBP displays that are compact, low power, and computationally efficient.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.