Results 1 to 10 of about 1,231,296 (158)

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. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various ...
Garsden, H., Girard, J., Starck, J., Corbel, S., Tasse, C., Woiselle, A., McKean, J., van Amesfoort, A., Anderson, J., Avruch, I., Beck, R., Bentum, M., Best, P., Breitling, F., Broderick, J., Brüggen, M., Butcher, H., Ciardi, B., de Gasperin, F., de Geus, E., de Vos, M., Duscha, S., Eislöffel, J., Engels, D., Falcke, H., Fallows, R., Fender, R., Ferrari, C., Frieswijk, W., Garrett, M., Grießmeier, J., Gunst, A., Hassall, T., Heald, G., Hoeft, M., Hö, el, J., van der Horst, A., Juette, E., Karastergiou, A., Kondratiev, V., Kramer, M., Kuniyoshi, M., Kuper, G., Mann, G., Markoff, S., McFadden, R., McKay-Bukowski, D., Mulcahy, D., Munk, H., Norden, M., Orru, E., Paas, H., ey-Pommier, M., ey, V., Pietka, G., Pizzo, R., Polatidis, A., Renting, A., Röttgering, H., Rowlinson, A., Schwarz, D., Sluman, J., Smirnov, O., Stappers, B., Steinmetz, M., Stewart, A., Swinbank, J., Tagger, M., Tang, Y., Tasse, C., Thoudam, S., Toribio, C., Vermeulen, R., Vocks, C., van Weeren, R., Wijnholds, S., Wise, M., Wucknitz, O., Yatawatta, S., Zarka, P., Zensus, A.   +81 more
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Sparse Image Reconstruction using Sparse Priors [PDF]

2006 International Conference on Image Processing, 2006
Sparse image reconstruction is of interest in the fields of radioastronomy and molecular imaging. The observation is assumed to be a linear transformation of the image, and corrupted by additive white Gaussian noise. We study the usage of sparse priors in the empirical Bayes framework: it permits the selection of the hyperparameters of the prior in a ...
Michael Ting, Raviv Raich, Alfred O. Hero III   +2 more
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Convolutional Sparse Coding for Trajectory Reconstruction [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
Trajectory basis Non-Rigid Structure from Motion (NRSfM) refers to the process of reconstructing the 3D trajectory of each point of a non-rigid object from just their 2D projected trajectories. Reconstruction relies on two factors: (i) the condition of the composed camera & trajectory basis matrix, and (ii) whether the trajectory basis has enough ...
Yingying Zhu 0004, Simon Lucey
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Collaborative sparse reconstruction for pan-sharpening [PDF]

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013
In this paper, we extend the Sparse Fusion of Images (SparseFI, pronounced “sparsify”) algorithm, proposed by the authors before, to a Jointly Sparse Fusion of Images (J-SparseFI) algorithm by exploiting the possible signal structural correlations between different multispectral channels. The algorithm is evaluated using airborne UltraCam data.
Xiaoxiang Zhu 0001, Claas Grohnfeldt, Richard Bamler   +2 more
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Sparse Shape Reconstruction [PDF]

SIAM Journal on Imaging Sciences, 2013
This paper introduces a new shape-based image reconstruction technique applicable to a large class of imaging problems formulated in a variational sense. Given a collection of shape priors (a shape dictionary), we define our problem as choosing the right elements and geometrically composing them through basic set operations to characterize desired ...
Alireza Aghasi, Justin K. Romberg
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Sparse Reconstruction by Separable Approximation [PDF]

IEEE Transactions on Signal Processing, 2008
Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), wavelet-based deconvolution and reconstruction, and compressed sensing (CS) are a few well-known areas in which problems of ...
Stephen J. Wright 0001, Robert D. Nowak, Mário A. T. Figueiredo   +2 more
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Sparse Image Reconstruction for Molecular Imaging [PDF]

IEEE Transactions on Image Processing, 2009
12 pages, 8 ...
Michael Ting, Raviv Raich, Alfred O. Hero III   +2 more
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Kernel Reconstruction ICA for Sparse Representation [PDF]

IEEE Transactions on Neural Networks and Learning Systems, 2015
Independent component analysis with soft reconstruction cost (RICA) has been recently proposed to linearly learn sparse representation with an overcomplete basis, and this technique exhibits promising performance even on unwhitened data. However, linear RICA may not be effective for the majority of real-world data because nonlinearly separable data ...
Yanhui Xiao, Zhenfeng Zhu, Yao Zhao 0001, Yunchao Wei, Shikui Wei   +4 more
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Sparse ACEKF for phase reconstruction

Optics Express, 2013
We propose a novel low-complexity recursive filter to efficiently recover quantitative phase from a series of noisy intensity images taken through focus. We first transform the wave propagation equation and nonlinear observation model (intensity measurement) into a complex augmented state space model.
Jingshan, Zhong, Dauwels, Justin, Vázquez, Manuel A, Waller, Laura   +3 more
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Sparse-View Ct Reconstruction Via Convolutional Sparse Coding [PDF]

2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019
Traditional dictionary learning based CT reconstruction methods are patch-based and the features learned with these methods often contain shifted versions of the same features. To deal with these problems, the convolutional sparse coding (CSC) has been proposed and introduced into various applications.
Peng Bao, Wenjun Xia, Kang Yang, Jiliu Zhou, Yi Zhang 0018   +4 more
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