Multi-resolution convolutional neural networks for inverse problems
| Autor: | Johannes Müller, Alberto Eljarrat, Trond R. Henninen, Christoph Koch, Feng Wang, Rolf Erni |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Noise reduction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Structure (category theory) lcsh:Medicine Image processing Imaging techniques 02 engineering and technology Translation (geometry) Characterization and analytical techniques Convolutional neural network Article Image (mathematics) Set (abstract data type) 0202 electrical engineering electronic engineering information engineering lcsh:Science Microscopy Multidisciplinary business.industry lcsh:R Pattern recognition Inverse problem 021001 nanoscience & nanotechnology Materials science Optics and photonics Computer Science::Computer Vision and Pattern Recognition lcsh:Q 020201 artificial intelligence & image processing Artificial intelligence 0210 nano-technology business |
| Zdroj: | Scientific Reports Scientific Reports, Vol 10, Iss 1, Pp 1-11 (2020) |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-020-62484-z |
| Popis: | Inverse problems in image processing, phase imaging, and computer vision often share the same structure of mapping input image(s) to output image(s) but are usually solved by different application-specific algorithms. Deep convolutional neural networks have shown great potential for highly variable tasks across many image-based domains, but sometimes can be challenging to train due to their internal non-linearity. We propose a novel, fast-converging neural network architecture capable of solving generic image(s)-to-image(s) inverse problems relevant to a diverse set of domains. We show this approach is useful in recovering wavefronts from direct intensity measurements, imaging objects from diffusely reflected images, and denoising scanning transmission electron microscopy images, just by using different training datasets. These successful applications demonstrate the proposed network to be an ideal candidate solving general inverse problems falling into the category of image(s)-to-image(s) translation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|