Results 111 to 120 of about 224 (152)

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,\;
Jiman Zhao, Zhao Jiman
exaly   +2 more sources

Texture classification using ridgelet transform

Pattern Recognition Letters, 2006
Texture classification has long been an important research topic in image processing. Now a day's 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, L Ganesan
exaly   +3 more sources

The finite ridgelet transform for image representation

IEEE Transactions on Image Processing, 2003
The ridgelet transform was introduced as a sparse expansion for functions on continuous spaces that are smooth away from discontinuities along lines. We propose an orthonormal version of the ridgelet transform for discrete and finite-size images. Our construction uses the finite Radon transform (FRAT) as a building block.
Minh Do, Martin Vetterli, M N Do
exaly   +5 more sources

The Ridgelet transform of distributions

Integral Transforms and Special Functions, 2014
Jasson Vindas, Stevan Pilipovic
exaly   +1 more source

3D fast ridgelet transform

Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2004
In this paper, we present a fast implementation of the 3D ridgelet transform based on discrete analytical 3D lines: the 3D discrete analytical ridgelet transform (DART). This transform uses the Fourier strategy (the projection-slice formula) for the computation of the associated discrete Radon transform.
Carré, Philippe, Helbert, David, Andrès, Éric   +2 more
openaire   +2 more sources

RIDGELET TRANSFORM ON SQUARE INTEGRABLE BOEHMIANS [PDF]

Bulletin of the Korean Mathematical Society, 2009
The ridgelet transform is extended to the space of square integrable Boehmians. It is proved that the extended ridgelet transform R is consistent with the classical ridgelet transform R, linear, one-to-one, onto and both R,R i1 are continuous with respect to --convergence as well as ¢-convergence.
Roopkumar Rajakumar
exaly   +2 more sources

Ridgelet transform for quarternion-valued functions

International Journal of Wavelets, Multiresolution and Information Processing, 2016
Using the convolution of quaternion-valued functions on [Formula: see text], we define the ridgelet transform on square integrable quaternion-valued functions on [Formula: see text]. We also prove the properties of the ridgelet transform such as linearity, continuity, Parseval’s identity and inversion formula.
Lakshmanan Akila, Rajakumar Roopkumar
openaire   +2 more sources

Generalized Discrete Radon Transforms and Their Use in the Ridgelet Transform

Journal of Mathematical Imaging and Vision, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Flavia Colonna, Glenn R. Easley
openaire   +3 more sources

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
openaire   +1 more source

Image enhancement by curvelet, ridgelet, and wavelet transform

SPIE Proceedings, 2010
Image Processing always aims at extracting maximum information from an image. To achieve this we have to analyze the image completely along its periphery. But the parts of an image are hardly straight, they contain continuously varying slopes. Wavelet based image processing gives low resolution when the image has largely varying slopes and they give
Vinay Mishra, Pallavi Parlewar
openaire   +2 more sources