Two Dimensional Magnetic Current Imaging Via L1-Curl Regularized Divergence Free Wavelet Reconstruction
Christopher Miller, Adrian Mariano, Sean Oliver, Jacob Lenz, Dmitro, Martynowych

TL;DR
This paper introduces a novel two-dimensional magnetic current imaging method using L1-curl regularization and divergence-free wavelet bases, improving reconstruction quality over traditional Fourier-based techniques.
Contribution
The paper proposes a new L1-curl regularization approach combined with divergence-free wavelet bases for better 2D magnetic current reconstruction.
Findings
Enhanced reconstruction accuracy on simulated data.
Improved noise robustness in laboratory magnetic field measurements.
Automatic enforcement of current continuity via wavelet basis.
Abstract
The reconstruction of current distributions from samples of their induced magnetic field is a challenging problem due to multiple factors. First, the problem of reconstructing general three dimensional current distributions is ill-posed. Second, the current-to-field operator performs a low-pass filter that dampens high-spatial frequency information, so that even in situations where the inversion is formally possible, attempting to employ the formal inverse will result in solutions with unacceptable noise. Most contemporary methods for reconstructing current distributions in two dimensions are based on Fourier techniques and apply a low pass filter to the -field data, which prevents excessive noise amplification during reconstruction at the cost of admitting blurring in the reconstructed solution. In this report, we present a method of current recovery based on penalizing the …
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Taxonomy
TopicsAdvanced MRI Techniques and Applications · Advanced X-ray and CT Imaging · Seismic Imaging and Inversion Techniques
