Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging

Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iter...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 22; číslo 15; s. 5533
Hlavní autori:	Hauffen, Jan Christian, Kästner, Linh, Ahmadi, Samim, Jung, Peter, Caire, Giuseppe, Ziegler, Mathias
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 25.07.2022 MDPI
Predmet:	3-D printers active thermal imaging Algorithms Applied mathematics block-sparsity Cameras deep unfolding defect reconstruction Defects Heat detection Inverse problems Investigations iterative shrinkage thresholding algorithm laser thermography Lasers Mathematical models Nondestructive testing Optimization techniques Regularization methods Sparsity Thermography
ISSN:	1424-8220, 1424-8220
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