Results 11 to 20 of about 4,760 (175)
Classification of the fibronectin variants with curvelets [PDF]
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018 The role of the extracellular matrix (ECM) in the evolution of certain diseases (e.g. fibrosis, cancer) is generally accepted but yet to be completely understood. A numerical model that captures the physical properties of the ECM, could convey certain connections between the topology of its constituents and their associated biological features.
Grapa, Anca-Ioana +7 more
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Utilizing the structure of a redundant dictionary comprised of wavelets and curvelets with compressed sensing [PDF]
J. Electronic Imaging, 2021 The discrete curvelet transform decomposes an image into a set of fundamental components that are distinguished by direction and size and a low-frequency representation.
N. Dwork, P. Larson
semanticscholar +1 more source
Texture retrieval using periodically extended and adaptive curvelets [PDF]
Signal processing. Image communication, 2019 Image retrieval is an important problem in the area of multimedia processing. This paper presents two new curvelet-based algorithms for texture retrieval suitable, which are suitable for use in constrained-memory devices.
H. Almarzouqi, Yuting Hu, G. Al-Regib
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Wavelets and curvelets transform for image denoising to damage identification of thin plate
Results in Engineering, 2023 As a common structural form, thin plates are widely used in civil engineering. Since the thin plate needs to face harsh work conditions, the damage inevitably to be accumulated, thus affecting the stability and safety of the application components ...
Deng Yulong +7 more
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Migration preconditioning with Curvelets [PDF]
SEG Technical Program Expanded Abstracts 2004, 2004 In this paper, the property of Curvelet transforms for preconditioning the migration and normal operators is investigated. These operators belong to the class of Fourier integral operators and pseudo-differential operators, respectively. The effect of this preconditioner is shown in term of improvement of sparsity, convergence rate, number of iteration
Moghaddam, Peyman P., Herrmann, Felix J.
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Accounting for observation errors in image data assimilation [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2015 This paper deals with the assimilation of image-type data. Such kinds of data, such as satellite images, have good properties (dense coverage in space and time), but also one crucial problem for data assimilation: they are affected by spatially ...
Vincent Chabot +3 more
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Face recognition based on curvelets, invariant moments features and SVM
, 2020 Recent studies highlighted on face recognition methods. In this paper, a new algorithm is proposed for face recognition by combining Fast Discrete Curvelet Transform (FDCvT) and Invariant Moments with Support vector machine (SVM), which improves rate of ...
M. Ghazal, Karam Abdullah
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Searching for cosmic strings in CMB anisotropy maps using wavelets and curvelets [PDF]
, 2016 We use wavelet and curvelet transforms to extract signals of cosmic strings from simulated cosmic microwave background (CMB) temperature anisotropy maps, and to study the limits on the cosmic string tension which various ongoing CMB temperature ...
L. Hergt +4 more
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The curvelet transform for image denoising [PDF]
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002 Summary form only given, as follows. We present approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform and the curvelet transform. Our implementations offer exact reconstruction, stability against perturbations, ease of implementation, and low computational complexity. We apply these digital transforms to
Jean-Luc Starck +2 more
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IEEE Signal Processing Magazine, 2010 Multiresolution methods are deeply related to image processing, biological and computer vision, and scientific computing. The curvelet transform is a multiscale directional transform that allows an almost optimal nonadaptive sparse representation of objects with edges.
Jianwei Ma, Gerlind Plonka
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