Results 11 to 20 of about 360 (169)
, 2009 Glossary WT1D The one-dimensional Wavelet Transform as defined in [1]. See also [2] in this volume. WT2D The two-dimensional Wavelet Transform. Discrete Ridgelet Trasnform (DRT) The discrete implementation of the continuous Ridgelet transform. Fast Slant Stack (FSS) An algebraically exact Radon transform of data on a Cartesian grid.
Fadili, Jalal M., Starck, Jean-Luc
core +5 more sources
BayesShrink Ridgelets for Image Denoising
, 2004 The 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
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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 +2 more
openaire +3 more sources
Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation. [PDF]
Int J Biomed Imaging, 2011 Copyright @ 2011 Shadi AlZubi et al. This article has been made available through the Brunel Open Access Publishing Fund.The experimental study presented in this paper is aimed at the development of an automatic image segmentation system for classifying ...
Alzubi S, Islam N, Abbod M.
europepmc +2 more sources
The Ridgelet transform of distributions [PDF]
Integral Transforms and Special Functions, 2013 We define and study the ridgelet transform of (Lizorkin) distributions. We establish connections with the Radon and wavelet transforms.
Kostadinova, Sanja +3 more
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Discrete analytical Ridgelet transform [PDF]
Signal Processing, 2004 In this paper, we present a new implementation of the Ridgelet transform based on discrete analytical 2-D lines: the discrete analytical Ridgelet transform (DART). This transform uses the Fourier strategy for the computation of the associated discrete Radon transform.
Carré, Philippe, Andres, Eric
openaire +1 more source
IET Radar, Sonar &Navigation, Volume 17, Issue 12, Page 1743-1759, December 2023., 2023 An overview of the past and current clutter theoretical models and clutter suppression techniques in the HFSWR system is provided. The experimental results involved in the complex long‐term ionosphere observation are discussed. Special attention is paid to the correlation between the signal degradation sources and eliminating clutter techniques ...
Xiaowei Ji +3 more
wiley +1 more source
Priors in Bayesian Deep Learning: A Review
International Statistical Review, Volume 90, Issue 3, Page 563-591, December 2022., 2022 Summary While the choice of prior is one of the most critical parts of the Bayesian inference workflow, recent Bayesian deep learning models have often fallen back on vague priors, such as standard Gaussians. In this review, we highlight the importance of prior choices for Bayesian deep learning and present an overview of different priors that have ...
Vincent Fortuin
wiley +1 more source
Robust medical zero‐watermarking algorithm based on Residual‐DenseNet
IET Biometrics, Volume 11, Issue 6, Page 547-556, November 2022., 2022 Abstract To solve the problem of poor robustness of existing traditional DCT‐based medical image watermarking algorithms under geometric attacks, a novel deep learning‐based robust zero‐watermarking algorithm for medical images is proposed. A Residual‐DenseNet is designed, which took low‐frequency features after discrete cosine transformation of ...
Cheng Gong +5 more
wiley +1 more source
Statistical quality control using image intelligence: A sparse learning approach
Naval Research Logistics (NRL), Volume 69, Issue 7, Page 996-1008, October 2022., 2022 Abstract Advances in image acquisition technology have made it convenient and economic to collect large amounts of image data. In manufacturing and service industries, images are increasingly used for quality control purposes because of their ability to quickly provide information about product geometry, surface defects, and nonconforming patterns.
Yicheng Kang
wiley +1 more source