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.
Highlights
Orthorectification is a process that orthorectifies an image onto its upright planimetry map and removes the perspective angle [1,2,3]
The orthorectification images obtained by field-programmable gate array (FPGA) and PC are not visually
This paper proposes an orthorectification method, namely, the field-programmable gate array (FPGA)-based fixed-point (FP) rational polynomial coefficient (RPC) method
Summary
Orthorectification is a process that orthorectifies an image onto its upright planimetry map and removes the perspective angle [1,2,3]. Orthorectification is a prerequisite for remotely sensed (RS) image applications in areas such as land resource investigation, disaster monitoring, forestry inventory, and environmental changes analysis. The RS image that is orthorectified contains the geometric accuracy of the map and has the features of the remote sensing image. 20 years, many orthorectification methods were proposed. Zhou et al [2] presented a comprehensive study on theories, algorithms, and methods of large-scale urban orthoimage generation. Zhou [3] proposed a near real-time orthorectification method for mosaic of video flow acquired by an unmanned aerial vehicle (UAV). Aguilar et al [4] used rigorous model and rational function model to orthorectify GeoEye-1 and WorldView-2 images and assessed the Sensors 2018, 18, 2511; doi:10.3390/s18082511 www.mdpi.com/journal/sensors
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