Optical single pixel detection with sampling functions utilizing prior knowledge
| Autor: | Rafal Kotynski, Krzysztof Czajkowski, Anna Pastuszczak |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Noise measurement
Computer science business.industry Multispectral image Sampling (statistics) Pattern recognition 02 engineering and technology Iterative reconstruction White noise 021001 nanoscience & nanotechnology 01 natural sciences 010309 optics Wavelet Compressed sensing Morlet wavelet Computer Science::Computer Vision and Pattern Recognition 0103 physical sciences Computer vision Artificial intelligence 0210 nano-technology business |
| Zdroj: | ICTON |
| Popis: | Single pixel detectors find applications ranging from multispectral imaging, through polarimetric, 3d, and holographic imaging, up to optical encryption and imaging through scattering media, which are however all hindered by the high measurement and reconstruction times. In this paper we propose to reduce the required signal acquisition time by using non-ergodic stationary sampling correlated with the measurement. The proposed sampling scheme after binarization can be used with binary spatial light modulators such as the digital micro-mirror devices. We report respective optical results obtained with a single-pixel detector with a state-of-the-art 21 kHz DMD. The proposed sampling method is based on a random selection of Morlet wavelet functions convolved with white noise. Our choice of sampling functions provides a trade-off between two contradictory objectives. One is the use sampling functions incoherent with the basis in which the image has a sparse representation, as is required in the compressive sensing framework. This is an argument for using random sampling. The other is to use sampling functions with the highest possible correlation with the image, which give a fast learning rate when some a priori information on the image is available. Here, wavelets are clearly preferable with respect to uncorrelated random patterns, and what we propose is a a trade-off between these two approaches. |
| Databáze: | OpenAIRE |
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