RPC-Based Orthorectification for Satellite Images Using FPGA
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-...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-08-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/8/2511 |
| _version_ | 1828391195908243456 |
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| author | Rongting Zhang Guoqing Zhou Guangyun Zhang Xiang Zhou Jingjin Huang |
| author_facet | Rongting Zhang Guoqing Zhou Guangyun Zhang Xiang Zhou Jingjin Huang |
| author_sort | Rongting Zhang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T06:57:26Z |
| format | Article |
| id | doaj.art-36e0a03b91c445bda2295495cae86c97 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T06:57:26Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-36e0a03b91c445bda2295495cae86c972022-12-22T01:58:24ZengMDPI AGSensors1424-82202018-08-01188251110.3390/s18082511s18082511RPC-Based Orthorectification for Satellite Images Using FPGARongting Zhang0Guoqing Zhou1Guangyun Zhang2Xiang Zhou3Jingjin Huang4School of Precision Instrument and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, ChinaSchool of Precision Instrument and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, ChinaThe Center for Remote Sensing, Tianjin University, Tianjin 300072, ChinaGuangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, ChinaSchool of Precision Instrument and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, ChinaConventional 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.http://www.mdpi.com/1424-8220/18/8/2511orthorectificationfield-programmable gate array (FPGA)rational polynomial coefficient (RPC) |
| spellingShingle | Rongting Zhang Guoqing Zhou Guangyun Zhang Xiang Zhou Jingjin Huang RPC-Based Orthorectification for Satellite Images Using FPGA Sensors orthorectification field-programmable gate array (FPGA) rational polynomial coefficient (RPC) |
| title | RPC-Based Orthorectification for Satellite Images Using FPGA |
| title_full | RPC-Based Orthorectification for Satellite Images Using FPGA |
| title_fullStr | RPC-Based Orthorectification for Satellite Images Using FPGA |
| title_full_unstemmed | RPC-Based Orthorectification for Satellite Images Using FPGA |
| title_short | RPC-Based Orthorectification for Satellite Images Using FPGA |
| title_sort | rpc based orthorectification for satellite images using fpga |
| topic | orthorectification field-programmable gate array (FPGA) rational polynomial coefficient (RPC) |
| url | http://www.mdpi.com/1424-8220/18/8/2511 |
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