Results 151 to 160 of about 5,751 (196)

Quaternion Ridgelet Transform and Curvelet Transform

Advances in Applied Clifford Algebras, 2018
The relationships between the Fourier, Radon, wavelet, ridgelet, curvelet transforms for real-valued functions have been extensively studied and are well known. The paper under review extends some of these relationships to quaternion-valued functions. A quaternion \(a\) can be represented as \[ a=a_0+a_1 i+a_2 j+a_3 k, \] with \[ ij=k,\; jk=i,\; ki=j,\;
Ma, Guangsheng, Zhao, Jiman
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Quaternionic curvelet transform

Optik, 2017
Abstract In this paper, we extend the continuous curvelet transform to the space of quaternion valued functions using convolution. We prove that the quaternionic curvelet transform is consistent with the continuous curvelet transform of complex valued functions.
L. Akila, R. Roopkumar
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3D discrete curvelet transform

SPIE Proceedings, 2005
In this paper, we present the first 3D discrete curvelet transform. This transform is an extension to the 2D transform described in Candes et al..1 The resulting curvelet frame preserves the important properties, such as parabolic scaling, tightness and sparse representation for singularities of codimension one.
Lexing Ying, Laurent Demanet, Emmanuel Candes   +2 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, T. G. SUBASH KUMAR, L. GANESAN   +2 more
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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., Abrial, P., Starck, Jean-Luc, Moudden, Y.   +3 more
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Curvelet transform with adaptive tiling

SPIE Proceedings, 2012
The curvelet transform is a recently introduced non-adaptive multi-scale transform that have gained popularity in the image processing field. In this paper, we study the effect of customized tiling of frequency content in the curvelet transform. Specifically, we investigate the effect of the size of the coarsest level and its relationship to denoising ...
Hasan Al-Marzouqi, Ghassan AlRegib
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Numeral recognition using curvelet transform

2008 IEEE/ACS International Conference on Computer Systems and Applications, 2008
This paper proposes the performance of two new algorithms for digit recognition. These recognition systems are based on extracted features on the performance of image's curvelet transform & achieving standard deviation and entropy of curvelet coefficients matrix in different scales & various angels.
Farhad Mohamad Kazemi, Jalaleddin Izadian, Reihane Moravejian, Ehsan Mohamad Kazemi   +3 more
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Curvelet transform on periodic distributions

Integral Transforms and Special Functions, 2014
The curvelet transform is defined on the spaces of infinitely differentiable periodic functions, periodic distributions and square integrable periodic functions and its properties are studied.
Rajendran Subash Moorthy, Rajakumar Roopkumar   +1 more
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Curvelet Transform Based Watermarking for Telemedicine

Wireless Personal Communications, 2021
Now a days telemedicine is a proactive research area and gaining more engrossment. Digital transmission of medical imaging, remote evaluation and diagnosis together are termed as Telemedcine and it has increasingly gained prominence in the recent times.
Rayachoti Eswaraiah, Tirumalasetty Sudhir, Prathipati Silpa Chaitanya   +2 more
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Localization operators for curvelet transforms

Journal of Pseudo-Differential Operators and Applications, 2011
The authors investigate the \(L^{2}\)-boundedness of three kinds of operators such as the localization operators for high frequencies, the wavelet multipliers for low frequencies and the curvelet localization operators for all signals. Also, they present a resolution of the identity formulas for high-frequency signals and study the trace class ...
Li, Jiawei, Wong, M. W.
openaire   +2 more sources