A physics-informed DIP method using a simple convolutional autoencoder reconstructs complex in-plane magnetization from NV magnetometry, with optimal mask orientation improving SNR by up to 3 dB.
Denoising Prior Driven Deep Neural Network for Im- age Restoration
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Physics-Informed Deep Image Prior Reconstruction of In-Plane Magnetization from Scanning NV Magnetometry
A physics-informed DIP method using a simple convolutional autoencoder reconstructs complex in-plane magnetization from NV magnetometry, with optimal mask orientation improving SNR by up to 3 dB.