Enhanced Low-Rank Matrix Decomposition for High-Resolution UAV-SAR Imagery

Low-rank matrix decomposition is effective for sparse recovery. However, the conventions are limited in accuracy for high-resolution synthetic aperture radar (SAR) imagery due to the shrinkage effect in the cost function, which leads to biased estimates. To this end, an enhanced-low rank matrix deco...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE journal on miniaturization for air and space systems 2024-09, Vol.5 (3), p.187-199
Hauptverfasser:	Gao, Bin, Song, Anna, Xu, Hanwen, Zhang, Zenan, Lian, Wenhui, Yang, Lei
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Alternating direction method of multipliers (ADMM) cooperative optimization Cost function Decomposition Effectiveness High resolution Image resolution low-rank matrix decomposition Matrix decomposition Optimization Phase transitions Radar imaging Radar polarimetry Regularization Singular value decomposition Synthetic aperture radar synthetic aperture radar (SAR) Vectors
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!