Diffracted image restoration: A machine learning approach
| Autor: | V. Koudelka, C. del Rio Bocio, Zbynek Raida |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Diffraction
Artificial neural network Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Image processing Machine learning computer.software_genre Connectionism Computer Science::Computer Vision and Pattern Recognition Computer vision Deconvolution Artificial intelligence business Image resolution computer Image restoration |
| Zdroj: | 2013 International Conference on Electromagnetics in Advanced Applications (ICEAA). |
| DOI: | 10.1109/iceaa.2013.6632375 |
| Popis: | Image restoration issues are closely connected with imaging systems, where image resolution is limited by diffraction phenomenon. The presented work is motivated by the super acuity of the Human vision, where the restoration step is implemented by some kind of parallel processor unit - neural network. The de-convolution process is formulated as a machine learning problem and the inverse operator is interpreted as a connectionist model. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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