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RPC-Based Orthorectification for Satellite Images Using FPGA.
Zhang, Rongting; Zhou, Guoqing; Zhang, Guangyun; Zhou, Xiang; Huang, Jingjin.
Affiliation
  • Zhang R; School of Precision Instrument and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, China. zrt65@tju.edu.cn.
  • Zhou G; Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China. zrt65@tju.edu.cn.
  • Zhang G; The Center for Remote Sensing, Tianjin University, Tianjin 300072, China. zrt65@tju.edu.cn.
  • Zhou X; School of Precision Instrument and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, China. gzhou@glut.edu.cn.
  • Huang J; Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China. gzhou@glut.edu.cn.
Sensors (Basel) ; 18(8)2018 Aug 01.
Article in En | MEDLINE | ID: mdl-30071668
ABSTRACT
Conventional rational polynomial coefficients (RPC)-based orthorectification methods are unable to satisfy the demands of timely responses to terrorist attacks and disaster rescue. To accelerate the orthorectification processing speed, we propose an on-board orthorectification method, i.e., a field-programmable gate array (FPGA)-based fixed-point (FP)-RPC orthorectification method. The proposed RPC algorithm is first modified using fixed-point arithmetic. Then, the FP-RPC algorithm is implemented using an FPGA chip. The proposed method is divided into three main modules a reading parameters module, a coordinate transformation module, and an interpolation module. Two datasets are applied to validate the processing speed and accuracy that are achievable. Compared to the RPC method implemented using Matlab on a personal computer, the throughputs from the proposed method and the Matlab-based RPC method are 675.67 Mpixels/s and 61,070.24 pixels/s, respectively. This means that the proposed method is approximately 11,000 times faster than the Matlab-based RPC method to process the same satellite images. Moreover, the root-mean-square errors (RMSEs) of the row coordinate (ΔI), column coordinate (ΔJ), and the distance ΔS are 0.35 pixels, 0.30 pixels, and 0.46 pixels, respectively, for the first study area; and, for the second study area, they are 0.27 pixels, 0.36 pixels, and 0.44 pixels, respectively, which satisfies the correction accuracy requirements in practice.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2018 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2018 Type: Article Affiliation country: China