Results 1 to 10 of about 7,799,574 (379)

LOFAR Sparse Image Reconstruction [PDF]

Astronomy & Astrophysics, 2015
Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness.
Anderson, J., Avruch, I., Beck, R., Bentum, M., Best, P., Breitling, F., Broderick, J., Brüggen, M., Butcher, H., Ciardi, B., Corbel, S., de Gasperin, F., de Geus, E., de Vos, M., Duscha, S., Eislöffel, J., el, J., Engels, D., ey, V., ey-Pommier, M., Falcke, H., Fallows, R., Fender, R., Ferrari, C., Frieswijk, W., Garrett, M., Garsden, H., Girard, J., Grießmeier, J., Gunst, A., Hassall, T., Heald, G., Hoeft, M., Hö,, Juette, E., Karastergiou, A., Kondratiev, V., Kramer, M., Kuniyoshi, M., Kuper, G., Mann, G., Markoff, S., McFadden, R., McKay-Bukowski, D., McKean, J., Mulcahy, D., Munk, H., Norden, M., Orru, E., Paas, H., Pietka, G., Pizzo, R., Polatidis, A., Renting, A., Rowlinson, A., Röttgering, H., Schwarz, D., Sluman, J., Smirnov, O., Stappers, B., Starck, J., Steinmetz, M., Stewart, A., Swinbank, J., Tagger, M., Tang, Y., Tasse, C., Tasse, C., Thoudam, S., Toribio, C., van Amesfoort, A., van der Horst, A., van Weeren, R., Vermeulen, R., Vocks, C., Wijnholds, S., Wise, M., Woiselle, A., Wucknitz, O., Yatawatta, S., Zarka, P., Zensus, A.   +81 more
core   +17 more sources

On Hallucinations in Tomographic Image Reconstruction [PDF]

IEEE Transactions on Medical Imaging, 2021
Tomographic image reconstruction is generally an ill-posed linear inverse problem. Such ill-posed inverse problems are typically regularized using prior knowledge of the sought-after object property. Recently, deep neural networks have been actively investigated for regularizing image reconstruction problems by learning a prior for the object ...
Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio   +3 more
openaire   +6 more sources

Image Reconstruction in Optical Interferometry [PDF]

IEEE Signal Processing Magazine, 2009
This tutorial paper describes the problem of image reconstruction from interferometric data with a particular focus on the specific problems encountered at optical (visible/IR) wavelengths.
Giovannelli, Jean-François, Thiébaut, Éric   +1 more
core   +12 more sources

Image reconstruction by domain transform manifold learning [PDF]

Nature, 2017
Image reconstruction plays a critical role in the implementation of all contemporary imaging modalities across the physical and life sciences including optical, MRI, CT, PET, and radio astronomy. During an image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an ...
Bo Zhu, Jeremiah Zhe Liu, B. Rosen, M. Rosen   +3 more
arxiv   +2 more sources

A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction [PDF]

arXiv, 2017
Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2D cardiac magnetic resonance (MR) images from undersampled data using a deep cascade of convolutional neural networks (CNNs) to accelerate the data acquisition process.
Jo Schlemper, Jose Caballero, J. Hajnal, A. Price, D. Rueckert   +4 more
arxiv   +3 more sources

Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction [PDF]

Heliyon
Background: Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction.
Varin Jaruvongvanich, Kobkun Muangsomboon, Wanwarang Teerasamit, Voraparee Suvannarerg, Chulaluk Komoltri, Sastrawut Thammakittiphan, Wimonrat Lornimitdee, Witchuda Ritsamrej, Parinya Chaisue, Napapong Pongnapang, Piyaporn Apisarnthanarak   +10 more
doaj   +2 more sources

Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction [PDF]

Computer Vision and Pattern Recognition, 2021
Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system.
Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, R. Timofte, L. Gool   +7 more
semanticscholar   +1 more source

Review of Super-Resolution Image Reconstruction Algorithms [PDF]

Jisuanji kexue yu tansuo, 2022
In human visual perception system, high-resolution (HR) image is an important medium to clearly express its spatial structure, detailed features, edge texture and other information, and it has a very wide range of practical value in medicine, criminal ...
ZHONG Mengyuan, JIANG Lin
doaj   +1 more source

RealFusion 360° Reconstruction of Any Object from a Single Image [PDF]

Computer Vision and Pattern Recognition, 2023
We consider the problem of reconstructing a full 360° photographic model of an object from a single image of it. We do so by fitting a neural radiance field to the image, but find this problem to be severely ill-posed.
Luke Melas-Kyriazi, Iro Laina, C. Rupprecht, A. Vedaldi   +3 more
semanticscholar   +1 more source

Review of Image Super-resolution Reconstruction Algorithms Based on Deep Learning [PDF]

Jisuanji kexue yu tansuo, 2022
The essence of image super-resolution reconstruction technology is to break through the limitation of hardware conditions, and reconstruct a high-resolution image from a low-resolution image which contains less infor-mation through the image super ...
YANG Caidong, LI Chengyang, LI Zhongbo, XIE Yongqiang, SUN Fangwei, QI Jin
doaj   +1 more source