Steerable Principal Components for Space-Frequency Localized Images

DOI10.1137/16M1085334zbMath1365.65041arXiv1608.02702WikidataQ42614089 ScholiaQ42614089MaRDI QIDQ5266383

Boris Landa, Yoel Shkolnisky

Publication date: 2 June 2017

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1608.02702

zbMATH Keywords

principal component analysiserror boundprolate spheroidal wave functionssteerable filtersgroup invarianceband limited functionsquadrature integration schemescientific image datasets

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical quadrature and cubature formulas (65D32) Lamé, Mathieu, and spheroidal wave functions (33E10)

Related Items (6)

Fast Expansion into Harmonics on the Disk: A Steerable Basis with Fast Radial Convolutions ⋮ Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit ⋮ On the eigenvalue distribution of spatio-spectral limiting operators in higher dimensions ⋮ Sampling and approximation of bandlimited volumetric data ⋮ The Steerable Graph Laplacian and its Application to Filtering Image Datasets ⋮ Method of moments for 3D single particleab initiomodeling with non-uniform distribution of viewing angles

Uses Software

• NFFT
• NFFT3

Cites Work

• Unnamed Item
• Prolate spheroidal wave functions of order zero. Mathematical tools for bandlimited approximation
• Prolate spheroidal wave functions on a disc -- integration and approximation of two-dimensional bandlimited functions
• Recurrence relations and fast algorithms
• Eigenvalue distribution of time and frequency limiting
• Group-theoretical methods in image understanding
• On Szegö's eigenvalue distribution theorem and non-Hermitian kernels
• Approximation scheme for essentially bandlimited and space-concentrated functions on a disk
• Necessary density conditions for sampling an interpolation of certain entire functions
• Prolate spheroidal wavefunctions, quadrature and interpolation
• Using NFFT 3---A Software Library for Various Nonequispaced Fast Fourier Transforms
• Steerable PCA for Rotation-Invariant Image Recognition
• Fast Fourier Transforms for Nonequispaced Data
• Accelerating the Nonuniform Fast Fourier Transform
• Nonuniform fast fourier transforms using min-max interpolation
• Computing Steerable Principal Components of a Large Set of Images and Their Rotations
• Prolate Spheroidal Wave Functions, Fourier Analysis and Uncertainty - I
• Prolate Spheroidal Wave Functions, Fourier Analysis and Uncertainty - II
• Prolate Spheroidal Wave Functions, Fourier Analysis and Uncertainty-III: The Dimension of the Space of Essentially Time- and Band-Limited Signals
• Prolate Spheroidal Wave Functions, Fourier Analysis and Uncertainty - IV: Extensions to Many Dimensions; Generalized Prolate Spheroidal Functions

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