PIMR: Parallel and Integrated Matching for Raw Data

Sensors

Zhenghao Li²  Junying Yang²  Jiaduo Zhao²  Peng Han¹  Zhi Chai³ 

[1] 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;Beijing Institute of Environmental Features, Beijing 100854, China;

关键词: image sensor;    raw data;    image matching;    image analysis;   

DOI  :  10.3390/s16010054

来源: mdpi

【 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】

CC BY   
© 2016 by the authors; licensee MDPI, Basel, Switzerland.