Super-resolution imaging via sparsity constraint and sparse speckle illumination
| Autor: | Wei Li, Wenlin Gong, Zunwang Bo, Chenglong Wang, Pengwei Wang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
business.industry Computer science Resolution (electron density) General Physics and Astronomy Reconstruction algorithm Superresolution Image (mathematics) Constraint (information theory) 03 medical and health sciences Speckle pattern 030104 developmental biology Quality (physics) Computer Science::Computer Vision and Pattern Recognition Computer vision Artificial intelligence Reconstructed image business |
| Zdroj: | Chinese Physics B. 27:074202 |
| ISSN: | 1674-1056 |
| DOI: | 10.1088/1674-1056/27/7/074202 |
| Popis: | We present an imaging approach via sparsity constraint and sparse speckle illumination which can dramatically enhance the optical system's imaging resolution. When the object is illuminated by some sparse speckles and the sparse reconstruction algorithm is utilized to restore the blur image, numerical simulated results demonstrate that the image, whose resolution exceeds the Rayleigh limit, can be stably reconstructed even if the detection signal-to-noise ratio (SNR) is less than 10 dB. Factors affecting the quality of the reconstructed image, such as the coded pattern's sparsity and the detection SNR, are also studied. |
| Databáze: | OpenAIRE |
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