Abstract
With 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.
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CITATION STYLE
Li, Z., Yang, J., Zhao, J., Han, P., & Chai, Z. (2016). PIMR: Parallel and integrated matching for raw data. Sensors (Switzerland), 16(1). https://doi.org/10.3390/s16010054
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