Computational Optical Sensing and Imaging 2021: introduction to the feature issue

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2021-03-01

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Ke, Jun
Alieva, Tatiana
Öktem, Sevinç Figen
Silveira, Paulo E. X.
Wetzstein, Gordon
Willomitzer, Florian

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This feature issue includes two reviews and 34 research papers that highlight recent works in the field of computational optical sensing and imaging. Many of the works were presented at the 2021 Optica (formerly OSA) Topical Meeting on Computational Optical Sensing and Imaging, held virtually from 19 July to 23 July 2021. Papers in the feature issue cover a broad scope of computational imaging topics, such as microscopy, 3D imaging, phase retrieval, non-line-of-sight imaging, imaging through scattering media, ghost imaging, compressed sensing, and applications with new types of sensors. Deep learning approaches for computational imaging and sensing are also a focus of this feature issue. (C) 2022 Optica Publishing Group

URI

https://hdl.handle.net/11511/97290

Journal

APPLIED OPTICS

DOI

https://doi.org/10.1364/ao.456133

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Department of Electrical and Electronics Engineering, Article

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Computational optical sensing and imaging 2021: feature issue introduction Ke, Jun; Alieva, Tatiana; Öktem, Sevinç Figen; Silveira, Paulo E.X.; Wetzstein, Gordon; Willomitzer, Florian (2022-03-28) © 2022 Optica Publishing GroupThis Feature Issue includes 2 reviews and 34 research articles that highlight recent works in the field of Computational Optical Sensing and Imaging. Many of the works were presented at the 2021 OSA Topical Meeting on Computational Optical Sensing and Imaging, held virtually from July 19 to July 23, 2021. Articles in the feature issue cover a broad scope of computational imaging topics, such as microscopy, 3D imaging, phase retrieval, non-line-of-sight imaging, imaging through ...
Absorbance Estimation and Gas Emissions Detection in Hyperspectral Imagery Başkurt, Nur Didem; Gur, Yusuf; Omruuzun, Fatih; Çetin, Yasemin (2016-05-19) Hyperspectral imaging in gas detection applications is a leading and widely studied research topic thanks to its high spectral resolution and remote detection ability. The main problems in these applications covers the leakage detection, gas identification, and quantification. The proposed algorithm aims to reach the transmittance and absorbance features of the gas and to detect the gaseous region by using the measured radiance data from the hyperspectral infrared sensors.
Numerical design and investigation of plasmonic lenses for maximum power focusing Güler, Sadri; Sür, Cem Gürkan; Ergül, Özgür Salih (2018-04-13) We present the design and investigation of plasmonic lenses to achieve maximum power focusing for imaging applications. As opposed to commonly used slits opened on metallic structures, the designs are based on different arrangements of holes on metallic slabs. The structures are obtained via an optimization environment based on a three-dimensional numerical solver using an efficient implementation of the multilevel fast multipole algorithm (MLFMA) and optimization modules using genetic algorithm. We demonst...
Experimental evaluation of cable drum systems as linear motion sensors KILIÇ, ERGİN; Dölen, Melik; Koku, Ahmet Buğra (2011-04-15) This study evaluates cable-drum mechanisms as linear motion sensors for certain CNC applications. In this work, the dynamical attributes of a generic device are studied experimentally. The conducted research indicates that despite the significant traction force induced between the cable and its drum, small fluctuations in mechanism's speed yields a considerable (micro) slip at the interface.
Feature detection and matching towards augmented reality applications on mobile devices Gündoğdu, Erhan; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2012) Local feature detection and its applications in different problems are quite popular in vision research. In order to analyze a scene, its invariant features, which are distinguishable in many views of this scene, are used in pose estimation, object detection and augmented reality. However, required performance metrics might change according to the application type; in general, the main metrics are accepted as accuracy and computational complexity. The contributions in this thesis provide improving these met...

Citation Formats

J. Ke, T. Alieva, S. F. Öktem, P. E. X. Silveira, G. Wetzstein, and F. Willomitzer, “Computational Optical Sensing and Imaging 2021: introduction to the feature issue,” APPLIED OPTICS, vol. 61, no. 9, pp. 0–0, 2021, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/97290.