Edge detection from non-uniform Fourier data using the convolutional gridding algorithm

DOI10.1007/s10915-014-9836-yzbMath1307.65026OpenAlexW2042499282MaRDI QIDQ487699

Adam Martinez, Anne Gelb, Alexander J. Gutierrez

Publication date: 23 January 2015

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2286/R.I.27998

zbMATH Keywords

numerical examplesimage processingmagnetic resonance imagingedge detectionreconstruction algorithmsFourier datanon-uniform fast Fourier transformconvolutional gridding

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical methods for discrete and fast Fourier transforms (65T50)

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Sequential image recovery from noisy and under-sampled Fourier data ⋮ Detecting edges from non-uniform Fourier data using Fourier frames ⋮ Joint Sparse Recovery Based on Variances ⋮ Edge Detection of Piecewise Smooth Functions from UnderSampled Fourier Data Using Variance Signatures ⋮ Nonuniform sampling, reproducing kernels, and the associated Hilbert spaces ⋮ Recovering Piecewise Smooth Functions from Nonuniform Fourier Measurements ⋮ Detecting edges from non-uniform Fourier data via sparse Bayesian learning

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