Results 21 to 30 of about 726,843 (203)

Otherness feature extraction method for underground image based on Shearlet transform

open access: yesGong-kuang zidonghua, 2016
For the problem that face images collected underground are susceptible to dust interference and most feature extraction methods are sensitive to noise, an otherness feature extraction method for underground image based on Shearlet transform was proposed.
HUANG Yu, ZHANG Yingjun, PAN Lihu
doaj   +2 more sources

Bendlet Transform Based Adaptive Denoising Method for Microsection Images [PDF]

open access: yesEntropy, 2022
Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise that appears in MRI images is commonly governed by a Rician distribution. The bendlets system is a second-order shearlet transform with bent elements.
Shuli Mei   +5 more
doaj   +2 more sources

A Convolution-Based Shearlet Transform in Free Metaplectic Domains

open access: yesJournal of Mathematics, 2021
The free metaplectic transformation (FMT) is a multidimensional integral transform that encompasses a broader range of integral transforms, from the classical Fourier to the more recent linear canonical transforms. The aim of this study is to introduce a
Tarun K. Garg   +3 more
doaj   +3 more sources

Light Field Reconstruction Using Shearlet Transform [PDF]

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
12 pages, 11 ...
Suren Vagharshakyan   +2 more
openaire   +7 more sources

Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning

open access: yesJournal of Imaging, 2016
The Gleason grading system is generally used for histological grading of prostate cancer. In this paper, we first introduce using the Shearlet transform and its coefficients as texture features for automatic Gleason grading.
Hadi Rezaeilouyeh, Mohammad H. Mahoor
doaj   +3 more sources

Image fusion based on shift invariant shearlet transform and stacked sparse autoencoder

open access: yesJournal of Algorithms & Computational Technology, 2018
Stacked sparse autoencoder is an efficient unsupervised feature extraction method, which has excellent ability in representation of complex data. Besides, shift invariant shearlet transform is a state-of-the-art multiscale decomposition tool, which is ...
Peng-Fei Wang   +3 more
doaj   +2 more sources

Continuity properties of the shearlet transform and the shearlet synthesis operator on the Lizorkin type spaces

open access: yesMathematische Nachrichten, 2022
AbstractWe develop a distributional framework for the shearlet transform and the shearlet synthesis operator , where is the Lizorkin test function space and is the space of highly localized test functions on the standard shearlet group . These spaces and their duals are called Lizorkin type spaces of test functions and distributions.
Francesca Bartolucci   +2 more
exaly   +5 more sources

A novel MRI PET image fusion using shearlet transform and pulse coded neural network [PDF]

open access: yesScientific Reports
Image fusion involves combining details from two or more different imaging techniques, say MRI and PET images and provides a better image for diagnosis and treatment. Despite the fact standard spatial domain methods are being used successfully, including
Vella Satyanarayana, P. Mohanaiah
doaj   +2 more sources

Image Sequence Fusion and Denoising Based on 3D Shearlet Transform [PDF]

open access: yesJournal of Applied Mathematics, 2014
We propose a novel algorithm for image sequence fusion and denoising simultaneously in 3D shearlet transform domain. In general, the most existing image fusion methods only consider combining the important information of source images and do not deal ...
Liang Xu, Junping Du, Zhenhong Zhang
doaj   +2 more sources

Shearlet Transform Applied to a Prostate Cancer Radiomics Analysis on MR Images

open access: yesMathematics
For decades, wavelet theory has attracted interest in several fields in dealing with signals. Nowadays, it is acknowledged that it is not very suitable to face aspects of multidimensional data like singularities and this has led to the development of ...
Rosario Corso   +3 more
doaj   +3 more sources

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