Results 61 to 70 of about 6,617 (256)

CHILDHOOD MEDULLOBLASTOMA DIAGNOSIS USING MULTISCALE FRAMEWORK

open access: yesInternational Journal of Advances in Signal and Image Sciences, 2022
This paper proposes an efficient Shearlet Based Childhood MedulloBlastoma (SBCMB) detection system. It is a classification system that extracts prominent characteristics for childhood MedulloBlastoma diagnosis from a given collection of histopathological
Vishal Eswaran, Usha Eswaran
doaj   +1 more source

Irregular Shearlet Frames: Geometry and Approximation Properties

open access: yes, 2010
Recently, shearlet systems were introduced as a means to derive efficient encoding methodologies for anisotropic features in 2-dimensional data with a unified treatment of the continuum and digital setting.
Kittipoom, P., Kutyniok, G., Lim, W.
core   +2 more sources

Shearlet-Based Structure-Aware Filtering for Hyperspectral and LiDAR Data Classification

open access: yesJournal of remote sensing, 2021
The joint interpretation of hyperspectral images (HSIs) and light detection and ranging (LiDAR) data has developed rapidly in recent years due to continuously evolving image processing technology. Nowadays, most feature extraction methods are carried out
S. Jia, Z. Zhan, Meng Xu
semanticscholar   +1 more source

Inhomogeneous shearlet coorbit spaces [PDF]

open access: yesInternational Journal of Wavelets, Multiresolution and Information Processing, 2018
In this paper, we establish inhomogeneous coorbit spaces related to the continuous shearlet transform and the weighted Lebesgue spaces [Formula: see text] for certain weights [Formula: see text]. We present an inhomogeneous shearlet frame for [Formula: see text] which gives rise to a reproducing kernel [Formula: see text] that is not contained in the ...
Fabian Feise, Lukas Sawatzki
openaire   +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   +1 more source

Introduction to Shearlets [PDF]

open access: yes, 2012
Shearlets emerged in recent years among the most successful frameworks for the efficient representation of multidimensional data. Indeed, after it was recognized that traditional multiscale methods are not very efficient at capturing edges and other anisotropic features which frequently dominate multidimensional phenomena, several methods were ...
Gitta Kutyniok, Demetrio Labate
openaire   +1 more source

Use of the Shearlet Transform and Transfer Learning in Offline Handwritten Signature Verification and Recognition [PDF]

open access: yesSahand Communications in Mathematical Analysis, 2020
Despite the growing growth of technology, handwritten signature has been selected as the first option between biometrics by users. In this paper, a new methodology for offline handwritten signature verification and recognition based on the Shearlet ...
Atefeh Foroozandeh   +2 more
doaj   +1 more source

ShearLab: A Rational Design of a Digital Parabolic Scaling Algorithm [PDF]

open access: yes, 2011
Multivariate problems are typically governed by anisotropic features such as edges in images. A common bracket of most of the various directional representation systems which have been proposed to deliver sparse approximations of such features is the ...
Gitta Kutyniok   +4 more
core   +1 more source

Multivariate $\alpha$-molecules

open access: yes, 2016
The suboptimal performance of wavelets with regard to the approximation of multivariate data gave rise to new representation systems, specifically designed for data with anisotropic features.
Flinth, Axel, Schäfer, Martin
core   +1 more source

A Robust Reversible Watermarking Algorithm Resistant to Geometric Attacks Based on Tchebichef Moments

open access: yesIET Image Processing, Volume 20, Issue 1, January/December 2026.
This paper presents a robust reversible watermarking algorithm based on Chebyshev moments, employing a two‐stage embedding mechanism. The proposed method leverages image block partitioning to embed the copyright watermark and the reversible watermark into non‐overlapping regions located inside and outside the inscribed circle of the image, respectively.
Wenjing Sun, Ling Zhang, Hongjun Zhang
wiley   +1 more source

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