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Sparse-Promoting 3-D Airborne Electromagnetic Inversion Based on Shearlet Transform
IEEE Transactions on Geoscience and Remote Sensing, 2022The conventional, L2-norm-based, regularization term in electromagnetic (EM) inversions implements smooth constraints on model complexity in the space domain, which can smoothen the boundaries of complex underground structures.
Yang Su +7 more
semanticscholar +1 more source
Deep Shearlet Network for Change Detection in SAR Images
IEEE Transactions on Geoscience and Remote Sensing, 2022Convolutional neural networks (CNNs) can extract shift-invariant features and have been widely applied in the change detection task. However, common CNN lacks noise robustness and needs supervised data to alleviate these problems; in this article, we ...
Huihui Dong +6 more
semanticscholar +1 more source
IEEE Transactions on Instrumentation and Measurement, 2019
As an effective way to integrate the information contained in multiple medical images with different modalities, medical image fusion has emerged as a powerful technique in various clinical applications such as disease diagnosis and treatment planning ...
M. Yin, Xiaoning Liu, Yu Liu, Xun Chen
semanticscholar +1 more source
As an effective way to integrate the information contained in multiple medical images with different modalities, medical image fusion has emerged as a powerful technique in various clinical applications such as disease diagnosis and treatment planning ...
M. Yin, Xiaoning Liu, Yu Liu, Xun Chen
semanticscholar +1 more source
Edges and Corners With Shearlets
IEEE Transactions on Image Processing, 2015Shearlets are a relatively new and very effective multi-scale framework for signal analysis. Contrary to the traditional wavelets, shearlets are capable to efficiently capture the anisotropic information in multivariate problem classes. Therefore, shearlets can be seen as the valid choice for multi-scale analysis and detection of directional sensitive ...
DUVAL POO, MIGUEL ALEJANDRO +2 more
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IEEE Transactions on Image Processing, 2009
In this paper, a new type of deconvolution algorithm is proposed that is based on estimating the image from a shearlet decomposition. Shearlets provide a multidirectional and multiscale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets.
Vishal M. Patel +2 more
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In this paper, a new type of deconvolution algorithm is proposed that is based on estimating the image from a shearlet decomposition. Shearlets provide a multidirectional and multiscale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets.
Vishal M. Patel +2 more
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International Journal of Neural Systems, 2020
Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and parallel computing model, combining the spiking and coupled mechanisms of neurons.
Bo Li +6 more
semanticscholar +1 more source
Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and parallel computing model, combining the spiking and coupled mechanisms of neurons.
Bo Li +6 more
semanticscholar +1 more source
Regularized Full-Waveform Inversion With Shearlet Transform and Total Generalized Variation
IEEE Transactions on Geoscience and Remote SensingFull-waveform inversion (FWI) is a powerful method of reconstructing subsurface properties during seismic exploration. However, it is difficult for FWI to accurately describe a subsurface model with sharp surfaces and smooth variations because of the ...
Hanyang Wang, Siwei Yu
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Shearlets: Theory and Applications
GAMM-Mitteilungen, 2014AbstractMany important problem classes are governed by anisotropic features such as singularities concentrated on lower dimensional embedded manifolds, for instance, edges in images or shock fronts in solutions of transport dominated equations. While the ability to reliably capture and sparsely represent anisotropic structures is obviously the more ...
Wang-Q Lim +2 more
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Detection of COVID-19 With CT Images Using Hybrid Complex Shearlet Scattering Networks
IEEE journal of biomedical and health informatics, 2021With the ongoing worldwide coronavirus disease 2019 (COVID-19) pandemic, it is desirable to develop effective algorithms to automatically detect COVID-19 with chest computed tomography (CT) images. Recently, a considerable number of methods based on deep
Qingyun Ren +3 more
semanticscholar +1 more source
Oberwolfach Reports, 2011
Over the last 20 years, multiscale methods and wavelets have revolutionized the field of applied mathematics by providing an efficient means for encoding isotropic phenomena. Directional multiscale systems, particularly shearlets, are now having the same dramatic impact on the encoding of multivariate signals.
Demetrio Labate, Gitta Kutyniok
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Over the last 20 years, multiscale methods and wavelets have revolutionized the field of applied mathematics by providing an efficient means for encoding isotropic phenomena. Directional multiscale systems, particularly shearlets, are now having the same dramatic impact on the encoding of multivariate signals.
Demetrio Labate, Gitta Kutyniok
openaire +2 more sources