Results 81 to 90 of about 157 (131)
Estimating fiber orientation distribution from diffusion MRI with spherical needlets. [PDF]
Med Image Anal, 2018 Yan H +4 more
europepmc +1 more source
Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python. [PDF]
Front Neuroinform, 2014 Rey-Villamizar N +8 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Image denoising with complex ridgelets
Pattern Recognition, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
G Y Chen, B Kegl
exaly +3 more sources
Ridge Functions and Orthonormal Ridgelets
Journal of Approximation Theory, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David Donoho
exaly +4 more sources
Wavelets, ridgelets and curvelets on the sphere [PDF]
Astronomy and Astrophysics, 2006 Accepted for publication in A&A.
Y Moudden
exaly +4 more sources
On the approximation of functions with line singularities by ridgelets [PDF]
Journal of Approximation Theory, 2019 58 pages, 2 ...
Philipp Grohs
exaly +6 more sources
Ridgelets and the Representation of Mutilated Sobolev Functions [PDF]
SIAM Journal on Mathematical Analysis, 2001 Summary: We show that ridgelets, a system introduced in [\textit{E. J. Candès}, Appl. Comput. Harmon. Anal. 6, No. 2, 197-218 (1999; Zbl 0931.68104)], are optimal to represent smooth multivariate functions that may exhibit linear singularities. For instance, let \(\{u\cdot x - b >0\}\) be an arbitrary hyperplane and consider the singular function \(f(x)
Emmanuel Candes
exaly +4 more sources
Iris Recognition Using Ridgelets [PDF]
Journal of Information Processing Systems, 2012 Abstract —Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris.
Lenina Birgale, Manesh Kokare
exaly +2 more sources