Deep learning optical image denoising research based on principal component estimation

High-quality denoising of optical interference images usually requires preliminary prediction of the noise level. Although blind denoising can filter the image at the pixel level without noise prediction, it inevitably loses a significant amount of phase information. This paper proposes a fast and h...

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Veröffentlicht in:	Applied optics (2004) 2022-05, Vol.61 (15), p.4412-4420
Hauptverfasser:	Lu, Qianbo, Liu, Chengxiu, Feng, Wenlu, Xiao, Qingxiong, Wang, Xiaoxu
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Complexity Image filters Image processing Image quality Interference Machine learning Mapping Neural networks Noise Noise levels Noise prediction Noise reduction Principal components analysis
Online-Zugang:	Volltext
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