Results 11 to 20 of about 1,177,560 (190)

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
openaire   +13 more sources

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
openaire   +5 more sources

Improved sparse representation using adaptive spatial support for effective target detection in hyperspectral imagery [PDF]

, 2013
With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui, Ren, Jinchang, Marshall, Stephen, Zhao, Chunhui   +3 more
core   +4 more sources

Sparse Reconstruction for Near-Field MIMO Radar Imaging Using Fast Multipole Method

IEEE Access, 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 ...
Emre A. Miran, Figen S. Oktem, Sencer Koc   +2 more
doaj   +1 more source

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
openaire   +3 more sources

A Sparse Reconstruction Algorithm for Ultrasonic Images in Nondestructive Testing [PDF]

Sensors, 2015
Lucia Valeria Arruda, Daniel Rodrigues Pipa, Giovanni Alfredo Guarneri   +2 more
exaly   +2 more sources

Dynamic Orthogonal Matching Pursuit for Sparse Data Reconstruction

IEEE Open Journal of Signal Processing, 2023
The orthogonal matching pursuit (OMP) is one of the mainstream algorithms for sparse data reconstruction or approximation. It acts as a driving force for the development of several other greedy methods for sparse data reconstruction, and it also plays a ...
Yun-Bin Zhao, Zhi-Quan Luo
doaj   +1 more source

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
openaire   +1 more source

Multi-Objective Sparse Reconstruction With Transfer Learning and Localized Regularization

IEEE Access, 2020
Multi-objective sparse reconstruction methods have shown strong potential in sparse reconstruction. However, most methods are computationally expensive due to the requirement of excessive functional evaluations.
Bai Yan, Qi Zhao, J. Andrew Zhang, Zhihai Wang   +3 more
doaj   +1 more source

ANALYSIS-BASED SPARSE RECONSTRUCTION WITH SYNTHESIS-BASED SOLVERS [PDF]

, 2012
© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Plumbley, MD, Jafari, MG, Cleju, N, IEEE
core   +4 more sources