Optimized Binary Patterns by Gradient Descent for Ghost Imaging
| Autor: | Tomoyoshi Ito, Tomoyoshi Shimobaba, Ikuo Hoshi, Takashi Kakue |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
General Computer Science
Image quality business.industry Computer science single-pixel imaging General Engineering ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Iterative reconstruction Ghost imaging TK1-9971 Noise Undersampling Robustness (computer science) Computer Science::Computer Vision and Pattern Recognition General Materials Science Computer vision Artificial intelligence Electrical engineering. Electronics. Nuclear engineering Gradient descent business Image resolution optimization gradient descent |
| Zdroj: | IEEE Access, Vol 9, Pp 97320-97326 (2021) |
| ISSN: | 2169-3536 |
| Popis: | Ghost imaging reconstructs images using a single-element photodetector; it performs imaging by illuminating an object with binary modulation patterns. This technique has various advantages, including a wide wavelength, noise robustness, and high measurement sensitivity. However, one challenge is the low image quality in the undersampling. The examination of modulation patterns is intended to solve this issue. In ghost imaging, randomly generated or basis patterns have been studied as modulation patterns; however, in undersampling, random patterns exhibit noise robustness but low image quality, whereas basis patterns exhibit high image quality but are sensitive to noise and low resolution. Thus, ghost imaging requires patterns that simultaneously achieve high image quality, resolution, and noise robustness. This study proposes a method of pattern optimization using gradient descent and a binarization method to further improve image quality. Numerical simulation and experimental results show that the proposed approach offers high image quality, high resolution, and robustness to noise. |
| Databáze: | OpenAIRE |
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