Fluorescence microscopy images denoising via deep convolutional sparse coding

Fluorescence microscopy images captured in low light and short exposure time conditions are always contaminated by photons and readout noises, which reduce the fluorescence microscopy images quality. In most cases, this kind of noise can be modeled as Poisson–Gaussian noise. Correspondingly, its den...

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Vydáno v:	Signal processing. Image communication Ročník 117; s. 117003
Hlavní autoři:	Chen, Ge, Wang, Jianjun, Wang, Hailin, Wen, Jinming, Gao, Yi, Xu, Yongjian
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.09.2023
Témata:	Deep convolutional neural network Deep learning Dilated convolution Fluorescence microscopy images denoising Multi-layer convolutional sparse coding Fluorescence microscopy images denoising Deep learning Dilated convolution Deep convolutional neural network Multi-layer convolutional sparse coding
ISSN:	0923-5965, 1879-2677
On-line přístup:	Získat plný text
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