All-optical image denoising using a diffractive visual processor

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-en...

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Veröffentlicht in:Light, science & applications science & applications, 2024-02, Vol.13 (1), p.43-43, Article 43
Hauptverfasser: Işıl, Çağatay, Gan, Tianyi, Ardic, Fazil Onuralp, Mentesoglu, Koray, Digani, Jagrit, Karaca, Huseyin, Chen, Hanlong, Li, Jingxi, Mengu, Deniz, Jarrahi, Mona, Akşit, Kaan, Ozcan, Aydogan
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Sprache:eng
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Zusammenfassung:Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans
ISSN:2047-7538
2095-5545
2047-7538
DOI:10.1038/s41377-024-01385-6