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Physics Letters A, 2003
In 1952 Toraldo di Francia [Il Nuovo Cimento (Suppl.) 9 (1952) 426] proposed an intriguing concept to increase the optical resolving power. As a consequence, this theory could seem in contradiction with Heisenberg's uncertainty principle. In this Letter we report on the results of a microwave investigation which demonstrate the rightness of such ...
Mugnai D, Ranfagni A, Ruggeri R
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In 1952 Toraldo di Francia [Il Nuovo Cimento (Suppl.) 9 (1952) 426] proposed an intriguing concept to increase the optical resolving power. As a consequence, this theory could seem in contradiction with Heisenberg's uncertainty principle. In this Letter we report on the results of a microwave investigation which demonstrate the rightness of such ...
Mugnai D, Ranfagni A, Ruggeri R
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On Hyperspectral Super-Resolution
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021In this paper we will review seminal contributions of Prof. Jose Bioucas Dias for the improvement of the spatial resolution of hyperspectral images. Be it through the extension of pansharpening algorithms with spatial and spectral sparsity priors, using spectral unmixing, using a low-rank assumption from complementary multisource data, or by designing ...
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Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2005
A robust approach for super-resolution is, presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion errors, inaccurate blur models, noise, moving objects, motion blur etc. This robustness is needed since super-resolution methods are very sensitive to such errors. A robust median estimator is combined in an
Assaf Zomet, Alex Rav-Acha, Shmuel Peleg
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A robust approach for super-resolution is, presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion errors, inaccurate blur models, noise, moving objects, motion blur etc. This robustness is needed since super-resolution methods are very sensitive to such errors. A robust median estimator is combined in an
Assaf Zomet, Alex Rav-Acha, Shmuel Peleg
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Super Resolution for Smartphones
Proceedings of the 13th International Joint Conference on e-Business and Telecommunications, 2016Smartphones were developed as an advanced communication tool. Currently they are used in various applications. The display is one of the most important features in smartphones. Compared with television (TV) and cinema screens the display size of a smartphone is small.
Seiichi Gohshi +4 more
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Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05., 2005
Abstract : Super-resolution algorithms produce a single high-resolution image from a set of several, low-resolution images of the desired scene. The low-resolution frames are shifted differently with respect to the high resolution frame with subpixel increments. This paper presents first a theoretical overview of super-resolution algorithms.
Christos Papathanassiou, Maria Petrou
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Abstract : Super-resolution algorithms produce a single high-resolution image from a set of several, low-resolution images of the desired scene. The low-resolution frames are shifted differently with respect to the high resolution frame with subpixel increments. This paper presents first a theoretical overview of super-resolution algorithms.
Christos Papathanassiou, Maria Petrou
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Super-resolution of mammograms
2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2010High-quality mammography is the most effective technology presently available for breast cancer screening. High resolution mammograms usually lead to more accurate diagnoses; however, they require large doses of radiation, which may have harmful effects.
Jun Zheng 0010 +2 more
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Proceedings IEEE International Symposium on Biomedical Imaging, 2003
In 2D multislice MRI, the resolution in the slice direction is often worse than the in-plane resolution. For certain diagnostic imaging applications, isotropic resolution is necessary but true 3D acquisition methods are not practical. In this case, if the imaging volume is acquired two or more times, with small spatial shifts between acquisitions ...
Hayit Greenspan +3 more
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In 2D multislice MRI, the resolution in the slice direction is often worse than the in-plane resolution. For certain diagnostic imaging applications, isotropic resolution is necessary but true 3D acquisition methods are not practical. In this case, if the imaging volume is acquired two or more times, with small spatial shifts between acquisitions ...
Hayit Greenspan +3 more
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Resolution and super‐resolution
Microscopy Research and Technique, 2017AbstractMany papers have claimed the attainment of super‐resolution, i.e. resolution beyond that achieved classically, by measurement of the profile of a feature in the image. We argue that measurement of the contrast of the image of a dark bar on a bright background does not give a measure of resolution, but of detection sensitivity.
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Nature Chemistry, 2019
The in situ, nanoscale positioning of a single molecule below the diffraction limit remains a challenge for chemists. Now, two approaches show how this can be accomplished through a combination of super-resolution microscopy and photo-inducible crosslinking chemistry.
Limin, Xiang, Ke, Xu
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The in situ, nanoscale positioning of a single molecule below the diffraction limit remains a challenge for chemists. Now, two approaches show how this can be accomplished through a combination of super-resolution microscopy and photo-inducible crosslinking chemistry.
Limin, Xiang, Ke, Xu
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Super-Sampling by Learning-Based Super-Resolution
International Journal of Computational Science and Engineering, 2018In this paper, we present a novel problem of intelligent image processing, which is how to infer a finer image in terms of intensity levels for a given image. We explain the motivation for this effort and present a simple technique that makes it possible to apply the existing learning-based super-resolution methods to this new problem.
Ping Du, Jinhuan Zhang, Jun Long
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