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Article

RPC-Based Orthorectification for Satellite Images Using FPGA

by 1,2,3, 1,2,3,4,*, 3, 2,3,4 and 1,2,3
1
School of Precision Instrument and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, China
2
Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
3
The Center for Remote Sensing, Tianjin University, Tianjin 300072, China
4
School of Microelectronics, Tianjin University, Tianjin 300072, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(8), 2511; https://doi.org/10.3390/s18082511
Received: 25 May 2018 / Revised: 20 July 2018 / Accepted: 28 July 2018 / Published: 1 August 2018
(This article belongs to the Special Issue High-Performance Computing in Geoscience and Remote Sensing)
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. View Full-Text
Keywords: orthorectification; field-programmable gate array (FPGA); rational polynomial coefficient (RPC) orthorectification; field-programmable gate array (FPGA); rational polynomial coefficient (RPC)
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MDPI and ACS Style

Zhang, R.; Zhou, G.; Zhang, G.; Zhou, X.; Huang, J. RPC-Based Orthorectification for Satellite Images Using FPGA. Sensors 2018, 18, 2511. https://doi.org/10.3390/s18082511

AMA Style

Zhang R, Zhou G, Zhang G, Zhou X, Huang J. RPC-Based Orthorectification for Satellite Images Using FPGA. Sensors. 2018; 18(8):2511. https://doi.org/10.3390/s18082511

Chicago/Turabian Style

Zhang, Rongting, Guoqing Zhou, Guangyun Zhang, Xiang Zhou, and Jingjin Huang. 2018. "RPC-Based Orthorectification for Satellite Images Using FPGA" Sensors 18, no. 8: 2511. https://doi.org/10.3390/s18082511

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