A new article is available in IPOL: http://www.ipol.im/pub/art/2022/425/
Roland Akiki, Carlo de Franchis, Gabriele Facciolo, Jean-Michel Morel,
and Raphaël Grandin,
Phase Unwrapping using a Joint CNN and SQD-LSTM Network,
Image Processing On Line, 12 (2022), pp. 378–388.
https://doi.org/10.5201/ipol.2022.425
Abstract
Phase unwrapping techniques are used in various applications, including
Synthetic Aperture Radar (SAR) interferometry (InSAR). Deep learning
methods have been recently proposed to tackle this problem. This work
aims at explaining and evaluating the method proposed by Perera et al.
in [A joint convolutional and spatial quad-directional LSTM network for
phase unwrapping, ICASSP 2021]. Furthermore, we provide an online demo
to simulate phase images and run them through the network. The network
performance can be tested visually and through metrics such as the error
standard deviation. The simulation can provide some out-of-distribution
data, especially with the added atmospheric signal specific to the InSAR
phase.
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