From Event: SPIE Commercial + Scientific Sensing and Imaging, 2018
Long image acquisition time is a critical problem in single-pixel-imaging. Here, we propose a new high-speed single-pixel compressive imaging method. We develop an ADMM based optimization algorithm to handle images with multiple features. The proposed method solves an optimization problem with the objectives of Total- Variation and ℓ1-norm with a data-fidelity constraint. The algorithm is highly parallel and is suitable for implementation using GPUs, with a significant reduction in computation. The resulting system produces high resolution images and can also be used for super-resolution by changing the single detector with a focal plane array. We verify the system experimentally and compare the performance of our algorithm with similar methods.
Oğuzhan Fatih Kar, Alper Güngör, Serhat İlbey, and H. Emre Güven, "An efficient parallel algorithm for single-pixel and FPA imaging," Proc. SPIE 10669, Computational Imaging III, 106690J (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 16, 2018; Published: 14 May 2018); https://doi.org/10.1117/12.2304342.
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