Results 31 to 40 of about 2,777 (169)
ShearLab 3D: Faithful Digital Shearlet Transforms based on Compactly Supported Shearlets [PDF]
, 2014 Wavelets and their associated transforms are highly efficient when approximating and analyzing one-dimensional signals. However, multivariate signals such as images or videos typically exhibit curvilinear singularities, which wavelets are provably ...
Kutyniok, Gitta +2 more
core +2 more sources
Curvelet transform for Boehmians
Arab Journal of Mathematical Sciences, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Subash Moorthy Rajendran +1 more
openaire +2 more sources
Detection and discrimination of cosmological non-Gaussian signatures by multi-scale methods
, 2003 Recent Cosmic Microwave Background (CMB) observations indicate that the temperature anisotropies arise from quantum fluctuations in the inflationary scenario. In the simplest inflationary models, the distribution of CMB temperature fluctuations should be
Aghanim +33 more
core +2 more sources
Face Recognition Using Curvelet Transform
, 2010 This paper presents a new method for the problem of human face recognition from still images. This is based on a multiresolution analysis tool called Digital Curvelet Transform. Curvelet transform has better directional and edge representation abilities than wavelets.
Hejazi, Hana, Alhanjouri, Mohammed A.
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Curvelet Based Feature Extraction [PDF]
, 2010 In this chapter, newly developed curvelet transform has been presented as a new tool for feature extraction from facial images. Various algorithms are discussed along with relevant experimental results as reported in some recent works on face recognition.
Guha, Tanaya, Wu, Q. M. Jonathan
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Fast Discrete Curvelet Transforms [PDF]
Multiscale Modeling & Simulation, 2006 This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions. The first digital transformation is based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected Fourier samples.
Candès, Emmanuel +3 more
openaire +2 more sources
Multi-scale geometric analysis of Lagrangian structures in isotropic turbulence [PDF]
, 2010 We report the multi-scale geometric analysis of Lagrangian structures in forced isotropic turbulence and also with a frozen turbulent field. A particle backward-tracking method, which is stable and topology preserving, was applied to obtain the ...
Bermejo-Moreno, Iván +2 more
core +1 more source
Second-Generation Curvelets on the Sphere [PDF]
, 2016 Curvelets are efficient to represent highly anisotropic signal content, such as a local linear and curvilinear structure. First-generation curvelets on the sphere, however, suffered from blocking artefacts.
Chan, JYH +3 more
core +2 more sources
Optimized Hybrid Deep Learning‐Based FPGA Accelerators for Denoising of Ultrasound Breast Images
IET Circuits, Devices &Systems, Volume 2026, Issue 1, 2026.This paper introduces a novel image‐denoising technique that integrates a hybrid deep learning (DL) model with a self‐improved orca predation (SOP) strategy. This hybrid model improves denoising performance by integrating a Convolutional Neural Network (CNN) with Bidirectional Long Short‐Term Memory (Bi‐LSTM).
K. Janaki +4 more
wiley +1 more source
Seismic Deconvolution Revisited with Curvelet Frames [PDF]
67th EAGE Conference & Exhibition, 2005 We propose an efficient iterative curvelet-regularized deconvolution algorithm that exploits continuity along reflectors in seismic images. Curvelets are a new multiscale transform that provides sparse representations for images (such as seismic images) that comprise smooth objects separated by piece-wise smooth discontinuities.
Hennenfent, Gilles +2 more
openaire +1 more source