PnP-MFAMP-Net: A Novel Plug-and-Play Sparse Reconstruction Network for SAR Imaging

Currently, the sparse imaging problem of synthetic aperture radar (SAR) is primarily addressed by compressed sensing (CS) theory, which introduces prior information into image restoration tasks via regularization. However, simple regularization constraints cannot provide the complex structural infor...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE geoscience and remote sensing letters 2024-01, Vol.21, p.1-1
Hauptverfasser:	Zhang, Hongwei, Ni, Jiacheng, Xiong, Shichao, Luo, Ying, Zhang, Qun
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms approximate message-passing (AMP) Approximation Computational modeling deep learning (DL) Image reconstruction Image restoration Imaging Imaging techniques Iterative methods Matched filters Message passing plug-and-play (PnP) Plugs Radar imaging Radar polarimetry Regularization Restoration Sampling SAR (radar) Scaling Signal-to-noise ratio sparse imaging Sparse matrices Synthetic aperture radar Synthetic aperture radar (SAR) Task complexity
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!