Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Figen S. Oktem"'
Publikováno v:
IEEE Access, Vol 9, Pp 151578-151589 (2021)
Radar imaging using multiple input multiple output systems are becoming popular recently. These applications typically contain a sparse scene and the imaging system is challenged by the requirement of high quality real-time image reconstruction from
Externí odkaz:
https://doaj.org/article/aeb8664ecda542c481c811d585582744
Publikováno v:
IEEE Access, Vol 9, Pp 151578-151589 (2021)
Radar imaging using multiple input multiple output systems are becoming popular recently. These applications typically contain a sparse scene and the imaging system is challenged by the requirement of high quality real-time image reconstruction from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7b4db740db6faeee578201d44072034
https://doi.org/10.1109/access.2021.3126472
https://doi.org/10.1109/access.2021.3126472
Autor:
Utku Gundogan, Figen S. Oktem
Publikováno v:
Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP).
We develop a joint reconstruction and system optimization method for snapshot spectral imaging with diffractive lenses. The method learns the diffractive lens design parameters jointly with a 3D deep prior in an unrolled reconstruction. Results illus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51a27df6794c034af3823ba6ce5d6751
https://doi.org/10.1364/cosi.2022.cw4b.4
https://doi.org/10.1364/cosi.2022.cw4b.4
Autor:
Jun Ke, Tatiana Alieva, Figen S. Oktem, Paulo E. X. Silveira, Gordon Wetzstein, Florian Willomitzer
Publikováno v:
E-Prints Complutense. Archivo Institucional de la UCM
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This 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 an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ef1c8bfd19865abac49036cc4876960
https://eprints.ucm.es/id/eprint/72000/1/AlievaT122libre+CC.pdf
https://eprints.ucm.es/id/eprint/72000/1/AlievaT122libre+CC.pdf
Autor:
Figen S. Oktem, Utku Gundogan
Publikováno v:
2021 IEEE International Conference on Image Processing (ICIP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::036bec80981f4c0a8f8ef70bf4586427
https://doi.org/10.1109/icip42928.2021.9506357
https://doi.org/10.1109/icip42928.2021.9506357
Autor:
Figen S. Oktem
Publikováno v:
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 27:3282-3295
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48b72ffe4ac1d0293aee2b028776e8a2
https://doi.org/10.3906/elk-1902-85
https://doi.org/10.3906/elk-1902-85
Autor:
Figen S. Oktem, Can Deniz Bezek
Publikováno v:
OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP).
We develop a novel deep learning-based reconstruction method for compressive spectral imaging with diffractive lenses. The method incorporates U-Net based 3D deep prior to the model-based reconstruction through unrolling. Results illustrate the state
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32a8124d1c2913e4e3c9e67f941110b1
https://doi.org/10.1364/cosi.2021.cm2e.3
https://doi.org/10.1364/cosi.2021.cm2e.3
Publikováno v:
SIU
Spectral imaging is a widely used diagnostic technique in various fields such as physics, chemistry, biology, medicine, astronomy, and remote sensing. In this work, we focus on a multi-spectral imaging technique with a diffractive lens, which relies
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73e8100e9bf38c55d177beb40af89474
https://doi.org/10.1109/siu49456.2020.9302259
https://doi.org/10.1109/siu49456.2020.9302259
Autor:
Utku Gundogan, Figen S. Oktem
Publikováno v:
SIU
Compressive spectral imaging is a technique that reconstructs the three-dimensional (3D) spectral data cube from limited number of two-dimensional (2D) measurements. In order to obtain this data cube, the technique makes use of the theory of compress
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd62ebcc931a5b8d128a78d3af66a9eb
https://doi.org/10.1109/siu49456.2020.9302220
https://doi.org/10.1109/siu49456.2020.9302220
Autor:
Didem Dogan, Figen S. Oktem
Publikováno v:
SIU
Many inverse problems in imaging involve measurements that are in the form of convolutions. Sparsity priors are widely exploited in their solutions for regularization as these problems are generally ill-posed. In this work, we develop image reconstru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b7943839e725f05f02757a28fc761c2
https://doi.org/10.1109/siu49456.2020.9302165
https://doi.org/10.1109/siu49456.2020.9302165