| Sensors | |
| PIMR: Parallel and Integrated Matching for Raw Data | |
| Zhi Chai1  Peng Han2  Jiaduo Zhao3  Zhenghao Li3  Junying Yang3  | |
| [1] Beijing Institute of Environmental Features, Beijing 100854, China;Chongqing Academy of Science and Technology, Chongqing 401123, China;Key Laboratory for Optoelectronic Technology and Systems of Ministry of Education, College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China; | |
| 关键词: image sensor; raw data; image matching; image analysis; | |
| DOI : 10.3390/s16010054 | |
| 来源: DOAJ | |
【 摘 要 】
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.
【 授权许可】
Unknown