Results 31 to 40 of about 35,538 (312)
A Compressed Sensing Framework for Magnetic Resonance Fingerprinting [PDF]
, 2014 Inspired by the recently proposed magnetic resonance fingerprinting (MRF) technique, we develop a principled compressed sensing framework for quantitative MRI. The three key components are a random pulse excitation sequence following the MRF technique, a
Wiaux, Yves; id_orcid +5 more
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Error Resilience for Block Compressed Sensing with Multiple-Channel Transmission
Applied Sciences, 2019 Compressed sensing is well known for its superior compression performance, in existing schemes, in lossy compression. Conventional research aims to reach a larger compression ratio at the encoder, with acceptable quality reconstructed images at the ...
Hsiang-Cheh Huang +2 more
doaj +1 more source
Compressed sensing applied to modeshapes reconstruction [PDF]
, 2011 Modal analysis classicaly used signals that respect the Shannon/Nyquist theory. Compressive sampling (or Compressed Sampling, CS) is a recent development in digital signal processing that offers the potential of high resolution capture of physical ...
Dimitri Bettebghor +3 more
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Compressed sensing for the detection of moving targets from short sequences of pulses: Special section "sparse reconstruction in remote sensing" [PDF]
, 2022 S.85-89The detection of ground moving targets from Mp ≈ 100 pulses of multichannel radar data allows the surveilance of wide areas. In this paper, their sparse distribution is utilized to produce a reconstruction of an angle-Doppler matrix using ...
Prünte, L.
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Leaf Classification for Crop Pests and Diseases in the Compressed Domain
Sensors, 2022 Crop pests and diseases have been the main cause of reduced food production and have seriously affected food security. Therefore, it is very urgent and important to solve the pest problem efficiently and accurately.
Jing Hua, Tuan Zhu, Jizhong Liu
doaj +1 more source
International Journal of Engineering Technologies and Management Research, 2020 Compressive sensing is a relatively new technique in the signal processing field which allows acquiring signals while taking few samples. It works on two principles: sparsity, which pertains to the signals of interest, and incoherence, which pertains to the sensing modality.
openaire +3 more sources
A Data-Adaptive Compressed Sensing Approach to Polarimetric SAR Tomography of Forested Areas [PDF]
, 2013 Super-resolution imaging via compressed sensing (CS)-based spectral estimators has been recently introduced to synthetic aperture radar (SAR) tomography.
Nannini, Matteo +2 more
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Sensors, 2021 Infrared images of power equipment play an important role in power equipment status monitoring and fault identification. Aiming to resolve the problems of low resolution and insufficient clarity in the application of infrared images, we propose a blind ...
Yan Wang +3 more
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Compressed quantitative MRI: Bloch response recovery through iterated projection [PDF]
, 2014 Inspired by the recently proposed Magnetic Resonance Fingerprinting technique, we develop a principled compressed sensing framework for quantitative MRI.
Wiaux, Yves; id_orcid +8 more
core +1 more source
Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems
International Journal of Antennas and Propagation, 2015 Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and ...
Taha A. Khalaf +2 more
doaj +1 more source