Results 91 to 100 of about 157 (131)
Some of the next articles are maybe not open access.
Neurocomputing, 2007
A ridgelet kernel regression method is presented in this paper to approximate multi-dimensional functions, especially those with certain kinds of spatial inhomogeneities. This method is based on ridgelet theory, kernel and regularization techniques from which we can deduce a regularized kernel regression form.
Shuyuan Yang 0001 +2 more
openaire +2 more sources
A ridgelet kernel regression method is presented in this paper to approximate multi-dimensional functions, especially those with certain kinds of spatial inhomogeneities. This method is based on ridgelet theory, kernel and regularization techniques from which we can deduce a regularized kernel regression form.
Shuyuan Yang 0001 +2 more
openaire +2 more sources
Neurocomputing, 2009
The multiscale properties of the reception field of the human visual cortex have illuminated the research of wavelet neural network (WNN). Findings in neurophysiology indicate that in the human visual system there are specialized areas in the visual cortex that respond for particular orientations.
Shuyuan Yang 0001 +2 more
openaire +1 more source
The multiscale properties of the reception field of the human visual cortex have illuminated the research of wavelet neural network (WNN). Findings in neurophysiology indicate that in the human visual system there are specialized areas in the visual cortex that respond for particular orientations.
Shuyuan Yang 0001 +2 more
openaire +1 more source
Wavelets, Ridgelets, and Curvelets for Poisson Noise Removal [PDF]
IEEE Transactions on Image Processing, 2008 In order to denoise Poisson count data, we introduce a variance stabilizing transform (VST) applied on a filtered discrete Poisson process, yielding a near Gaussian process with asymptotic constant variance. This new transform, which can be deemed as an extension of the Anscombe transform to filtered data, is simple, fast, and efficient in (very) low ...
Jean-Luc Starck, Jalāl M Fadili
exaly +6 more sources
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 +2 more
openaire +2 more sources
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 +2 more
openaire +2 more sources
Robust Digital Watermarking in the Ridgelet Domain
IEEE Signal Processing Letters, 2004In this letter, we propose a multiplicative watermarking method operating in the ridgelet domain. We employ the directional sensitivity and the anisotropy of the ridgelet transform (RT) in order to obtain a sparse image representation, where the most significant coefficients represent the most energetic direction of an image with straight edges ...
Patrizio Campisi +2 more
openaire +1 more source
BayesShrink Ridgelets for Image Denoising
2004The wavelet transform has been employed as an efficient method in image denoising via wavelet thresholding and shrinkage. The ridgelet transform was recently introduced as an alternative to the wavelet representation of two dimensional signals and image data.
Nezamoddin Nezamoddini-Kachouie +2 more
openaire +2 more sources
Ridgelet transform for quarternion-valued functions
International Journal of Wavelets, Multiresolution and Information Processing, 2016Using 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
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
openaire +2 more sources
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
openaire +2 more sources
Texture Classification Using Ridgelet Transform
Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05), 2006Texture 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.
Arivazhagan Selvaraj +2 more
openaire +2 more sources
Orthonormal Ridgelets and Linear Singularities
SIAM Journal on Mathematical Analysis, 2000Summary: We construct a new orthonormal basis for \(L^2({\mathbb R}^2)\), whose elements are angularly integrated ridge functions -- \textit{orthonormal ridgelets}. The basis elements are smooth and of rapid decay in the spatial domain, and in the frequency domain are localized near angular wedges which, at radius \(r = 2^j\), have radial extent ...
openaire +1 more source