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 |
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Format: | Artikel |
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 |
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ISSN: | 2047-7538 2095-5545 2047-7538 |
DOI: | 10.1038/s41377-024-01385-6 |