Linear independence of compactly supported separable shearlet systems
This paper examines linear independence of shearlet systems. This property has already been studied for wavelets and other systems such as, for instance, for Gabor systems.
Ma, Jackie, Petersen, Philipp
core +1 more source
Multimodal Biometrics: A Review of Handcrafted and AI–Based Fusion Approaches
As security threats continue to evolve, multimodal biometric recognition systems (MBRSs) have emerged as robust solutions for reliable user authentication. To the best of our knowledge, this study presents the first systematic literature review (SLR) specifically focused on MBRS based on physiological traits, combining traditional image processing ...
Hind Es-Sobbahi +3 more
wiley +1 more source
Detection and Characterisation of Atypical Harmonic Patterns in Big Power Quality Data
This paper proposes a new algorithm to identify and assess properties of atypical harmonic patterns in long‐term monitoring data adaptively. The well‐known challenges of field application, such as data accuracy validation, missing data handling, adaptability to dynamic data nature (seasonality and trends), and data mining results interpretation, are ...
Olga Zyabkina +6 more
wiley +1 more source
Sparse representation for restoring images by exploiting topological structure of graph of patches
To elevate sparse representation learning, this study leverages a graph learning model to delineate similarity relationships among image patches, utilizing this model for the initial image reconstruction phase. To capitalize on inter‐patch relationships while preserving individual patch characteristics, low‐rank constraints are integrated during the ...
Yaxian Gao +5 more
wiley +1 more source
ShearLab: A Rational Design of a Digital Parabolic Scaling Algorithm [PDF]
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
An Unsupervised Image Enhancement Method Based on Adaptation Region Divisions
This paper proposes an image enhancement method that combines traditional techniques with deep learning. It converts images to Lab color space, calculates texture complexity, adaptation region divisions and uses a convolutional autoencoder for noise reduction.
Kaijun Zhou, Weiyi Yuan, Yemei Qin
wiley +1 more source
Histopathology Image Enhancement Using Multi‐Resolution Deep Learning Techniques
Accurate analysis of histopathology images is critical for reliable disease diagnosis and effective treatment planning. However, the resolution limitations of digital pathology scanners can hinder the visibility of fine cellular details, potentially impacting diagnostic accuracy and patient outcomes. In this study, we present a comprehensive comparison
Meriem Touhami +4 more
wiley +1 more source
Analysis of time-frequency scattering transforms
In this paper we address the problem of constructing a feature extractor which combines Mallat's scattering transform framework with time-frequency (Gabor) representations. To do this, we introduce a class of frames, called uniform covering frames, which
Czaja, Wojciech, Li, Weilin
core +1 more source
Fake Fingerprint Classification Using Hybrid Features Learning With Gradient Boosting
Biometric security systems must be able to detect phony fingerprints to provide reliable authentication. The findings of this study suggest a hybrid approach to the detection of fake fingerprints that uses information on the texture and shape of the fingerprint.
Muhammad Salman Ali +7 more
wiley +1 more source
Analysis of Inpainting via Clustered Sparsity and Microlocal Analysis [PDF]
Recently, compressed sensing techniques in combination with both wavelet and directional representation systems have been very effectively applied to the problem of image inpainting.
King, Emily J. +2 more
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