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Per-pixel mirror-based method for high-speed video acquisition
Affiliation:1. Department of Computer Science, University of Brasilia, Brasilia, Brazil;2. University of Brasilia at Gama, Gama, Brazil;3. Department of Electrical Engineering, University of Brasilia, Brasilia, DF, Brazil;1. Facultad de Ingeniería, Universidad Autónoma de Querétaro, Río Moctezuma 249, Col. San Cayetano, 76807 San Juan del Río, Querétaro, Mexico;2. CIDETEQ, S.C., Parque Tecnológico Querétaro S/N, San Fandila, 76700 Pedro Escobedo, Querétaro, Mexico;1. Key Laboratory of Pattern Recognition and Intelligent Information Processing, Institutions of Higher Education of Sichuan Province, Chengdu University, 610104, PR China;2. College of Computer Science, Sichuan University, Chengdu 610065, PR China;3. School of Computer and Software, Sichuan University, Chengdu 610065, PR China;1. Sharif University of Technology, Tehran, Iran;2. University of Denver, CO, USA;1. National Tsing Hua University, Taiwan;2. National Chung Cheng University, Taiwan
Abstract:High-speed imaging requires high-bandwidth, fast image sensors that are generally only available in high-end specialized cameras. Nevertheless, with the use of compressive sensing theory and computational photography techniques, new methods emerged that use spatial light modulators to reconstruct high-speed videos with low speed sensors. Although these methods represent a big step in the field, they still present some limitations, such as low light efficiency and the generation of measurements with time dependency. To tackle these problems, we propose a per-pixel mirror-based acquisition method that is based on a new kind of light modulator. The proposed method uses moving mirrors to scramble the light coming from different positions, thus ensuring better light efficiency and generating time independent measurements. Our results show that the proposed method and its variations perform better than methods available in the literature, generating videos that are less noisy and that display better content separation.
Keywords:Compressive sensing  Computational photography  High-speed imaging
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