PIMR: Parallel and Integrated Matching for Raw Data
AbstractWith the trend of high-resolution imaging, computational costs of image matching have substantially increased. In order to find the compromise between accuracy and computation in real-time applications, we bring forward a fast and robust matching algorithm, named parallel and integrated matching for raw data (PIMR). This algorithm not only effectively utilizes the color information of raw data, but also designs a parallel and integrated framework to shorten the time-cost in the demosaicing stage. Experiments show that compared to existing state-of-the-art methods, the proposed algorithm yields a comparable recognition rate, while the total time-cost of imaging and matching is significantly reduced. View Full-Text
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Li, Z.; Yang, J.; Zhao, J.; Han, P.; Chai, Z. PIMR: Parallel and Integrated Matching for Raw Data. Sensors 2016, 16, 54.
Li Z, Yang J, Zhao J, Han P, Chai Z. PIMR: Parallel and Integrated Matching for Raw Data. Sensors. 2016; 16(1):54.Chicago/Turabian Style
Li, Zhenghao; Yang, Junying; Zhao, Jiaduo; Han, Peng; Chai, Zhi. 2016. "PIMR: Parallel and Integrated Matching for Raw Data." Sensors 16, no. 1: 54.
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