Results 141 to 150 of about 1,159 (170)
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Curvelets for surface characterization

Applied Physics Letters, 2007
Surface metrology is the science of measuring small-scale features on surfaces, which is important to many disciplines including tribology, fluid mechanics, optics, and manufacturing. Applications of wavelets on functional surfaces have become an increasing interest.
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Uniform Discrete Curvelet Transform

IEEE Transactions on Signal Processing, 2010
An implementation of the discrete curvelet transform is proposed in this work. The transform is based on and has the same order of complexity as the Fast Fourier Transform (FFT). The discrete curvelet functions are defined by a parameterized family of smooth windowed functions that satisfies two conditions: i) 2π periodic; ii) their squares form a ...
Truong T. Nguyen, Hervé Chauris
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Guided wave expansion in warped curvelet frames

IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2012
Lamb wave testing for structural health monitoring (SHM) often relies on analysis of wavefields recorded through scanning laser Doppler vibrometers (SLDVs) or ultrasonic scanners. Damage detection and characterization with these techniques requires isolation of defect-induced reflections in the wavefield from the injected wave packet and from ...
DE MARCHI, LUCA   +4 more
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TEXTURE CLASSIFICATION USING CURVELET TRANSFORM

International Journal of Wavelets, Multiresolution and Information Processing, 2007
Texture classification has long been an important research topic in image processing. Nowadays classification based on wavelet transform is being very popular. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities.
S. ARIVAZHAGAN   +2 more
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The monogenic curvelet transform

2010 IEEE International Conference on Image Processing, 2010
In this article, we reconsider the continuous curvelet transform from a signal processing point of view. We show that the analyzing elements of the curvelet transform, the curvelets, can be understood as analytic signals in the sense of the partial Hilbert transform.
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Curvelet transform on the sphere

IEEE International Conference on Image Processing 2005, 2005
Spherical maps occur in a range of applications for instance in geophysics or in astrophysics with the study of the cosmic microwave background (CMB) radiation field, where observations are over the whole sky. Analyzing these images requires specific tools.
Nguyen, Mai K.   +3 more
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Parabolic Molecules: Curvelets, Shearlets, and Beyond

2014
Anisotropic representation systems such as curvelets and shearlets have had a significant impact on applied mathematics in the last decade. The main reason for their success is their superior ability to optimally resolve anisotropic structures such as singularities concentrated on lower dimensional embedded manifolds, for instance, edges in images or ...
Grohs, Philipp   +3 more
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Curvelet Based Thinning Algorithm

2019
Efficiency of a recognition algorithm depends upon availability of noiseless and classes of images with unique and differentiable features. Thinning plays an important part in building a recognition system for various types of images. It is mainly used in handwritten character recognition systems and Biometric systems.
R. L. Jyothi, M. Abdul Rahiman
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Seismic imaging in the curvelet domain and its implications for the curvelet design

SEG Technical Program Expanded Abstracts 2006, 2006
This paper is a first attempt towards the migration of seismic data in the curvelet domain for heterogeneous background velocity models. We first explain how to build a simple curvelet decomposition/reconstruction code, based on the use of Fast Fourier Transforms (FFTs).
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Curvelet Transform Based Logo Watermarking

2007
Apart From Existing Representation Such As DCT, Wavelets, And Steerable Pyramids, Recently, Curvelet Is Introduced As A New Multiscale Presentation Suited For Images Which Are Smooth Away From Discontinuities Across Cuvers. In This Paper We Propose A New Watermarking Method Based On Curvelet Domain.
Thai Duy Hien   +4 more
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