Results 131 to 140 of about 547 (152)

Shearlet Transform and the Application in Image Processing

2022
Shearlet is a multi-dimensional function used for sparse representation, which has many excellent characteristics such as multi-resolution and multi-direction. It can detect the position of singular points and the direction of singular curves, and is more sensitive to the geometric structure of the image.
Haitao H., Cattani P., Guercio V., Villecco F.   +3 more
openaire   +2 more sources

The Radon transform intertwines wavelets and shearlets

Applied and Computational Harmonic Analysis, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bartolucci, Francesca, De Mari, Filippo, De Vito, Ernesto, Odone, Francesca   +3 more
openaire   +1 more source

A Microscopic Image Classification Method Using Shearlet Transform

2013 IEEE International Conference on Healthcare Informatics, 2013
This paper presents a method for representation and classification of microscopic tissue images using the shear let transform. The objective is to automatically process biopsy tissue images and assist pathologists in analyzing carcinoma cells, e.g. differentiating between benign and malignant cells in breast tissues.
Hadi Rezaeilouyeh, Mohammad H. Mahoor, Seyed Mohammad Mavadati, Jun Jason Zhang   +3 more
openaire   +1 more source

Multi-focus Image Fusion by Nonsubsampled Shearlet Transform

2011 Sixth International Conference on Image and Graphics, 2011
In this paper we introduce the nonsubsampled shear let transform for multi-focus image fusion. In the proposed method, source images are decomposed by nonsubsampled shear let transform firstly. Then the decomposition coefficients are merged according to the given fusion rule.
Yuan Cao 0001, Shutao Li 0001, Jianwen Hu   +2 more
openaire   +1 more source

Electroencephalogram signal classification based on shearlet and contourlet transforms

Expert Systems with Applications, 2017
Detection of epilepsy patterns in EEG signals with high accuracy.Development of a novel methodology based on curvelet and shearlet transforms.Extraction of a set of discriminative characteristics from the signals.Evaluation on a public data set.Results superior/comparable to the literature.
Paulo H. J. Amorim, Thiago F. Moraes, Dalton Ieda Fazanaro, Jorge Silva 0001, Hélio Pedrini   +4 more
openaire   +1 more source

A non-subsampled Shearlet transform based approach for heartbeat sound watermarking

Biomedical Signal Processing and Control, 2022
Amine Khaldi, Mohamed Redouane Kafi
exaly  

On Heisenberg and local uncertainty principles for the multivariate continuous quaternion Shearlet transform

Journal of Pseudo-Differential Operators and Applications, 2022
K Brahim, Bochra Nefzi
exaly  

Comparison of Wavelet and Shearlet Transforms for Medical Images

Applied Mathematics & Information Sciences, 2016
Sevindir, HÜLYA, YAZICI, CÜNEYT
openaire   +3 more sources

Noise suppression for microseismic data by non‐subsampled shearlet transform based on singular value decomposition

Geophysical Prospecting, 2018
Yue Li
exaly  

Uncertainty principles for the multivariate continuous shearlet transform

Journal of Pseudo-Differential Operators and Applications, 2019
K Brahim, Bochra Nefzi, Ahmed Fitouhi
exaly