Underwater Multispectral Computational Imaging Based on a Broadband Water-Resistant Sb2Se3 Heterojunction Photodetector.
Sign Up to like & getrecommendations! Published in 2022 at "ACS nano"
DOI: 10.1021/acsnano.1c10936
Abstract: Exploration, utilization, and protection of marine resources are of great significance to the survival and development of mankind. However, currently classical optical cameras suffer information loss, low contrast, and color distortion due to the absorption… read more here.
Keywords: imaging; photodetector; heterojunction photodetector; computational imaging ... See more keywords
Computational Imaging Prediction of Starburst-Effect Diffraction Spikes
Sign Up to like & getrecommendations! Published in 2018 at "Scientific Reports"
DOI: 10.1038/s41598-018-34400-z
Abstract: When imaging bright light sources, rays of light emanating from their centres are commonly observed; this ubiquitous phenomenon is known as the starburst effect. The prediction and characterization of starburst patterns formed by extended sources… read more here.
Keywords: prediction starburst; imaging prediction; starburst effect; computational imaging ... See more keywords
BlindNet: an untrained learning approach toward computational imaging with model uncertainty
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Physics D: Applied Physics"
DOI: 10.1088/1361-6463/ac2ad4
Abstract: The solution of an inverse problem in computational imaging (CI) often requires the knowledge of the physical model and/or the object. However, in many practical applications, the physical model may not be accurately characterized, leading… read more here.
Keywords: learning approach; model; untrained learning; computational imaging ... See more keywords
Multispectral Compressive Imaging Strategies Using Fabry–Pérot Filtered Sensors
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2018.2864659
Abstract: In this paper, we introduce two novel acquisition schemes for multispectral compressive imaging. Unlike most existing methods, the proposed computational imaging techniques do not include any dispersive element, as they use a dedicated sensor that… read more here.
Keywords: multispectral compressive; compressive imaging; fabry rot; computational imaging ... See more keywords
dO: A Differentiable Engine for Deep Lens Design of Computational Imaging Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2022.3212837
Abstract: Computational imaging systems algorithmically post-process acquisition images either to reveal physical quantities of interest or to increase image quality, e.g., deblurring. Designing a computational imaging system requires co-design of optics and algorithms, and recently Deep… read more here.
Keywords: deep lens; optics; imaging systems; differentiable engine ... See more keywords
Annular Computational Imaging: Capture Clear Panoramic Images Through Simple Lens
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2022.3233467
Abstract: Panoramic Annular Lens (PAL) composed of few lenses has great potential in panoramic surrounding sensing tasks for mobile and wearable devices because of its tiny size and large Field of View (FoV). However, the image… read more here.
Keywords: physics; imaging; design; annular computational ... See more keywords
Quantum-inspired computational imaging
Sign Up to like & getrecommendations! Published in 2018 at "Science"
DOI: 10.1126/science.aat2298
Abstract: More to imaging than meets the eye Traditional imaging techniques involve peering down a lens and collecting as much light from the target scene as possible. That requirement can set limits on what can be… read more here.
Keywords: quantum; quantum inspired; way; imaging ... See more keywords
Active computational imaging for circumventing resolution limits at macroscopic scales.
Sign Up to like & getrecommendations! Published in 2017 at "Applied optics"
DOI: 10.1364/ao.56.000d84
Abstract: Macroscopic imagers are subject to constraints imposed by the wave nature of light and the geometry of image formation. The former limits the resolving power while the latter results in a loss of absolute size… read more here.
Keywords: resolution limits; optics; circumventing resolution; active computational ... See more keywords
Combined hardware and computational optical wavefront correction.
Sign Up to like & getrecommendations! Published in 2018 at "Biomedical optics express"
DOI: 10.1364/boe.9.002562
Abstract: In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront… read more here.
Keywords: correction; wavefront correction; hardware computational; computational imaging ... See more keywords
A Two-step-training Deep Learning Framework for Real-time Computational Imaging without Physics Priors
Sign Up to like & getrecommendations! Published in 2021 at "Optics express"
DOI: 10.1364/oe.424165
Abstract: Deep learning (DL) is a powerful tool in computational imaging for many applications. A common strategy is to use a preprocessor to reconstruct a preliminary image as the input to a neural network to achieve… read more here.
Keywords: computational imaging; physics; model; step training ... See more keywords
Anti-noise computational imaging using unsupervised deep learning.
Sign Up to like & getrecommendations! Published in 2022 at "Optics express"
DOI: 10.1364/oe.470767
Abstract: Computational imaging enables spatial information retrieval of objects with the use of single-pixel detectors. By combining measurements and computational methods, it is possible to reconstruct images in a variety of situations that are challenging or… read more here.
Keywords: anti noise; unsupervised deep; imaging; deep learning ... See more keywords