On-Board Ortho-Rectification for Images Based on an FPGA
AbstractThe traditional ortho-rectification technique for remotely sensed (RS) images, which is performed on the basis of a ground image processing platform, has been unable to meet timeliness or near timeliness requirements. To solve this problem, this paper presents research on an ortho-rectification technique based on a field programmable gate array (FPGA) platform that can be implemented on board spacecraft for (near) real-time processing. The proposed FPGA-based ortho-rectification method contains three modules, i.e., a memory module, a coordinate transformation module (including the transformation from geodetic coordinates to photo coordinates, and the transformation from photo coordinates to scanning coordinates), and an interpolation module. Two datasets, aerial images located in central Denver, Colorado, USA, and an aerial image from the example dataset of ERDAS IMAGINE 9.2, are used to validate the processing speed and accuracy. Compared to traditional ortho-rectification technology, the throughput from the proposed FPGA-based platform and the personal computer (PC)-based platform are 11,182.3 kilopixels per second and 2582.9 kilopixels per second, respectively. This means that the proposed FPGA-based platform is 4.3 times faster than the PC-based platform for processing the same RS images. In addition, the root-mean-square errors of the planimetric coordinates φX and φY and the distance φS are 1.09 m, 1.61 m, and 1.93 m, respectively, which can meet the requirements of correction accuracy in practice. View Full-Text
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Zhou, G.Z.R.Z.N.L.J.H.X.; Zhang, R.; Liu, N.; Huang, J.; Zhou, X. On-Board Ortho-Rectification for Images Based on an FPGA. Remote Sens. 2017, 9, 874.
Zhou GZRZNLJHX, Zhang R, Liu N, Huang J, Zhou X. On-Board Ortho-Rectification for Images Based on an FPGA. Remote Sensing. 2017; 9(9):874.Chicago/Turabian Style
Zhou, Guoqing Z.R.Z.N.L.J.H.X.; Zhang, Rongting; Liu, Na; Huang, Jingjin; Zhou, Xiang. 2017. "On-Board Ortho-Rectification for Images Based on an FPGA." Remote Sens. 9, no. 9: 874.