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Related papers: Diffractive flat lens enables Extreme Depth-of-foc…

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Monocular depth estimation (MDE) aims to infer per-pixel depth from a single RGB image. While diffusion models have advanced MDE with impressive generalization, they often exhibit limitations in accurately reconstructing far-range regions.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Mingxia Zhan , Li Zhang , Yingjie Wang , Xiaomeng Chu , Beibei Wang , Yanyong Zhang

Perfect lensing using negative refractive index materials and radiationless electromagnetic interference both provide extreme subwavelength focusing by "amplifying" evanescent wave components that are usually lost. This paper provides a…

Optics · Physics 2015-06-03 Reuven Gordon

Lensless imaging is an elegant approach to high-resolution microscopy, which is rapidly gaining popularity in applications where imaging optics are problematic. However, current lensless imaging methods require objects to be placed within a…

Aberrations limit optical systems in many situations, for example when imaging in biological tissue. Machine learning offers novel ways to improve imaging under such conditions by learning inverse models of aberrations. Learning requires…

Optics · Physics 2021-04-30 Ivan Vishniakou , Johannes D. Seelig

A simple optical lens plays an important role for exploring the microscopic world in science and technology by refracting light with tailored spatially varying refractive index. Recent advancements in nanotechnology enable novel lenses,…

Optics · Physics 2014-11-25 Jianjun Cao , Ce Shang , Yuanlin Zheng , Xianfeng Chen , Xiaogan Liang , Wenjie Wan

Optical blur is an inherent property of any lens system and is challenging to model in modern cameras because of their complex optical elements. To tackle this challenge, we introduce a high-dimensional neural representation of…

Image and Video Processing · Electrical Eng. & Systems 2025-07-18 Esther Y. H. Lin , Zhecheng Wang , Rebecca Lin , Daniel Miau , Florian Kainz , Jiawen Chen , Xuaner Cecilia Zhang , David B. Lindell , Kiriakos N. Kutulakos

The emergence of far-field super-resolution microscopy has rejuvenated the possibility for nanoscale imaging. Approaches to far-field super-resolution that utilize point scanning often depends on spatially reducing the size of the focused…

Optics · Physics 2022-06-17 Ning Xu , Guoxuan Liu , Qiaofeng Tan

The rising prevalence of vision-threatening retinal diseases poses a significant burden on the global healthcare systems. Deep learning (DL) offers a promising solution for automatic disease screening but demands substantial data.…

Image and Video Processing · Electrical Eng. & Systems 2024-11-18 Ruoyu Chen , Weiyi Zhang , Bowen Liu , Xiaolan Chen , Pusheng Xu , Shunming Liu , Mingguang He , Danli Shi

Recent advances in metasurface lenses (metalenses) have shown great potential for opening a new era in compact imaging, photography, light detection and ranging (LiDAR), and virtual reality/augmented reality (VR/AR) applications. However,…

Optical imaging systems are generally limited by the depth of field because of the nature of the optics. Therefore, extending depth of field (EDoF) is a fundamental task for meeting the requirements of emerging visual applications. To solve…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Zhilong Li , Kejun Wu , Qiong Liu , You Yang

Defocus blur arises in images that are captured with a shallow depth of field due to the use of a wide aperture. Correcting defocus blur is challenging because the blur is spatially varying and difficult to estimate. We propose an effective…

Image and Video Processing · Electrical Eng. & Systems 2020-07-20 Abdullah Abuolaim , Michael S. Brown

The resolution of optical imaging devices is ultimately limited by the diffraction of light. To circumvent this limit, modern super-resolution microscopy techniques employ active interaction with the object by exploiting its optical…

Optics · Physics 2022-01-05 A. A. Pushkina , G. Maltese , J. I. Costa-Filho , P. Patel , A. I. Lvovsky

Over the recent years, there have been many reports of achromatic metalenses and diffractive lenses. However, very few (if any) practical applications of such achromatic flat lenses have been demonstrated, which raises questions about the…

Optics · Physics 2020-09-15 Jacob Engelberg , Uriel Levy

We propose an approach to far-field optical imaging beyond the diffraction limit. The proposed system allows image magnification, is robust with respect to material losses and can be fabricated by adapting existing metamaterial technologies…

Optics · Physics 2009-11-13 Zubin Jacob , Leonid V. Alekseyev , Evgenii Narimanov

Defocus blur is a common problem in photography. It arises when an image is captured with a wide aperture, resulting in a shallow depth of field. Sometimes it is desired, e.g., in portrait effect. Otherwise, it is a problem from both an…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Kunal Swami

We demonstrate visible and near-IR image projection via non-absorbing, multi-level Broadband Diffractive-Optical Elements (BDOEs) in 1 or more planes. By appropriate design of the BDOE topography, we experimentally demonstrate: (1)…

Optics · Physics 2020-02-19 Monjurul Meem , Apratim Majumder , Rajesh Menon

Light-field microscopy represents a promising solution for microscopic volumetric imaging, thanks to its capability to encode information on multiple planes in a single acquisition. This is achieved through its peculiar simultaneous capture…

A microwave lens with highly reduced reflectance, as compared to conventional dielectric lenses, is proposed. The lens is based on two-dimensional or three-dimensional transmission-line networks that can be designed to have an effective…

Optics · Physics 2009-11-13 Pekka Alitalo , Olli Luukkonen , Joni Vehmas , Sergei Tretyakov

The angular response of thin diffractive optical elements is highly correlated. For example, the angles of incidence and diffraction of a grating are locked through the grating momentum determined by the grating period. Other diffractive…

As an optical machine learning framework, Diffractive Deep Neural Networks (D2NN) take advantage of data-driven training methods used in deep learning to devise light-matter interaction in 3D for performing a desired statistical inference…

Image and Video Processing · Electrical Eng. & Systems 2020-07-08 Deniz Mengu , Yifan Zhao , Nezih T. Yardimci , Yair Rivenson , Mona Jarrahi , Aydogan Ozcan
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