Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning

Article English OPEN
Sun, Mingjie ; Edgar, Matthew P. ; Phillips, David B. ; Gibson, Graham M. ; Padgett, Miles J. (2016)
  • Publisher: OSA Publishing
  • Related identifiers: doi: 10.1364/OE.24.010476
  • Subject:
    arxiv: Computer Science::Computer Vision and Pattern Recognition
    acm: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION

Single-pixel cameras provide a means to perform imaging at wavelengths where pixelated detector arrays are expensive or limited. The image is reconstructed from measurements of the correlation between the scene and a series of masks. Although there has been much research in the field in recent years, the fact that the signal-to-noise ratio (SNR) scales poorly with increasing resolution has been one of the main limitations prohibiting the uptake of such systems. Microscanning is a technique that provides a final higher resolution image by combining multiple images of a lower resolution. Each of these low resolution images is subject to a sub-pixel sized lateral displacement. In this work we apply a digital microscanning approach to an infrared single-pixel camera. Our approach requires no additional hardware, but is achieved simply by using a modified set of masks. Compared to the conventional Hadamard based single-pixel imaging scheme, our proposed framework improves the SNR of reconstructed images by ∼ 50 % for the same acquisition time. In addition, this strategy also provides access to a stream of low-resolution ‘preview’ images throughout each high-resolution acquisition.
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