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Deconvolution based on the curvelet transform [PDF]
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2004 This paper describes a new deconvolution algorithm, based on both the wavelet transform and the curvelet transform. It extends previous results which were obtained for the denoising problem. Using these two different transformations in the same algorithm allows us to optimally detect in the same time isotropic features, well represented by the wavelet ...
Nguyen, Mai K. +2 more
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2D Empirical Transforms. Wavelets, Ridgelets, and Curvelets Revisited [PDF]
SIAM Journal of Imaging Sciences, 2014 A recently developed approach, called “empirical wavelet transform,” aims to build one-dimensional (1D) adaptive wavelet frames accordingly to the analyzed signal.
Jérôme Gilles, Giang Tran, S. Osher
semanticscholar +1 more source
Variational Multiscale Nonparametric Regression: Algorithms and Implementation
Algorithms, 2020 Many modern statistically efficient methods come with tremendous computational challenges, often leading to large-scale optimisation problems. In this work, we examine such computational issues for recently developed estimation methods in nonparametric ...
Miguel del Alamo +3 more
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BioTechniques, 2009 Cell migration plays a major role in development, physiology, and disease, and is frequently evaluated in vitro by the monolayer wound healing assay. The assay analysis, however, is a time-consuming task that is often performed manually.
Tobias Gebäck +3 more
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An Intertwining of Curvelet and Linear Canonical Transforms
Journal of Mathematics, 2020 In this article, we introduce a novel curvelet transform by combining the merits of the well-known curvelet and linear canonical transforms. The motivation towards the endeavour spurts from the fundamental question of whether it is possible to increase ...
Azhar Y. Tantary, Firdous A. Shah
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, 2009 Glossary WT1D The one-dimensional Wavelet Transform as defined in [1]. See also [2] in this volume. WT2D The two-dimensional Wavelet Transform. Discrete Ridgelet Trasnform (DRT) The discrete implementation of the continuous Ridgelet transform. Fast Slant Stack (FSS) An algebraically exact Radon transform of data on a Cartesian grid.
Fadili, Jalal M., Starck, Jean-Luc
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Edge detection in microscopy images using curvelets
BMC Bioinformatics, 2009 Background Despite significant progress in imaging technologies, the efficient detection of edges and elongated features in images of intracellular and multicellular structures acquired using light or electron microscopy is a challenging and time ...
Koumoutsakos Petros, Gebäck Tobias
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Compactly Supported Curvelet-Type Systems
Journal of Function Spaces and Applications, 2012 We study a flexible method for constructing curvelet-type frames. These curvelet-type systems have the same sparse representation properties as curvelets for appropriate classes of smooth functions, and the flexibility of the method allows us to give a ...
Kenneth N. Rasmussen, Morten Nielsen
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Local appearance-based face recognition using adaptive directional wavelet transform
Journal of King Saud University: Computer and Information Sciences, 2019 The latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity.
Mohd. Abdul Muqeet, Raghunath S. Holambe
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Curvelet Denoising of 4D Seismic [PDF]
66th EAGE Conference & Exhibition, 2004 With burgeoning world demand and a limited rate of discovery of new reserves, there is increasing impetus upon the industry to optimize recovery from already existing fields. 4D, or time-lapse, seismic imaging is an emerging technology that holds great promise to better monitor and optimise reservoir production. The basic idea behind 4D seismic is that
Bayreuther, Moritz +2 more
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