Results 161 to 170 of about 1,628 (189)

Monoscale Dual Ridgelet Frame

2005
A new system—Monoscale Dual Ridgelet Frame (MDRF) is constructed in this paper, which can be viewed as a generalized version of Monoscale Ridgelet introduced by Candes. The MDRT takes the Dual Ridgelet Frame as its basic component. We show that localizing the Dual Ridgelet Frame into small squares, dyadic partition of [0, 1]2, constitutes a dual frame ...
Tan Shan, Licheng Jiao
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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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Radon/ridgelet signature for image authentication

2004 International Conference on Image Processing, 2004. ICIP '04., 2005
In this paper, we describe a novel content-based image signature for authentication using the ridgelet transform. The signature is extracted from the Radon domain and entropy coded after a 1D wavelet transform, which is essentially the so-called "ridgelet transform". Unlike traditional authentication signatures, it has the ability to localise tampering
Zhen Yao, Nasir M. Rajpoot
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Ridgelet moment invariants for pattern recognition

2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012
Moment invariants have been a hot research topic for several decades already. Even though existing moment invariants are good for applications like pattern recognition, there is still a need to further improve the existing moment invariants published in the literature.
Guangyi Chen 0001, Scott Gleason 0001
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EXTENDED RIDGELET TRANSFORM ON DISTRIBUTIONS AND BOEHMIANS

Asian-European Journal of Mathematics, 2011
The ridgelet transform is extended to the space of Schwartz distributions and to the space of C∞-Boehmians consistent with the classical Ridgelet transform on the space of square integrable Boehmians. The properties of the ridgelet transform like linearity, injectivity, surjectivity and continuity with respect to two notions of convergence are ...
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Image denoising based on ridgelet

6th International Conference on Signal Processing, 2002., 2002
Image denoising is an important step in the pre-processing of images; the noisy images bears different characteristics. For an anisotropic image, wavelets lose their effects on singularity detection because discontinuities across edges are spatially distributed.
null Hou Biao, null Jiao Li-cheng, null Liu Fang   +2 more
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Fingerprint Compression by Ridgelet Transform

2008 IEEE International Symposium on Signal Processing and Information Technology, 2008
In the present paper, a concept of compression using block ridgelet transform is introduced. This kind of analysis/synthesis fingerprint representation takes the form of basis elements which exhibit very high directional sensitivity and are highly anisotropic.
Abdelhak Ouanane, Amina Serir
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On the Combination of Ridgelets Descriptors for Symbol Recognition

2008
In this paper we propose an original solution to combine the scales of multi-resolution shape descriptors. More precisely, a classifier fusion scheme is applied to a set of shape descriptors obtained from the ridgelets transform. The Ridgelets coefficients are grouped into different descriptors according to their resolution.
Oriol Ramos Terrades, Ernest Valveny, Salvatore Tabbone   +2 more
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A New Adaptive Ridgelet Neural Network

2005
In this paper, a new kind of neural network is proposed by combining ridgelet with feed-forward neural network (FNN). The network adopts ridgelet as the activation function in hidden layer of a three-layer FNN. Ridgelet is a good basis for describing the directional information in high dimension and it proves to be optimal in representing the functions
Shuyuan Yang 0001, Min Wang 0007, Licheng Jiao   +2 more
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A Novel Ridgelet Kernel Regression Method

2005
In this paper, a ridgelet kernel regression model is proposed for approximation of multivariate functions, especially those with certain kinds of spatial inhomogeneities. It is based on ridgelet theory, kernel and regularization technology from which we can deduce a regularized kernel regression form.
Shuyuan Yang 0001, Min Wang 0007, Licheng Jiao, Qing Li 0065   +3 more
openaire   +1 more source