Abstract
The 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.
Highlights
Given technological development, remotely sensed (RS) images can be acquired quickly and
Many traditional image processing systems, such as ENVI and ERDAS IMAGINE, are serial instruction systems based on personal computer (PC) computers
These original data and parameters are sent to the collinearity equation transformation module (CETM), affine transformation module (ATM), and interpolation module (IM) in the same clock cycle, when the enable signal is being received; The coefficients of the collinearity conditional equation, geodetic coordinates of the ortho-photo, and photo coordinates are calculated by the CETM
Summary
Remotely sensed (RS) images can be acquired quickly and . Jiang et al [2] proposed a scalable massively parallel fast research algorithm to reduce the computational cost of motion estimation and disparity estimation using a central processing unit (CPU)/ graphical processing unit (GPU). In these methods, the GPU and CPU are combined to process images. This paper is organized as follows: the structure of the proposed hardware platform based on an FPGA is described, and the experiments, comparison, and analyses are conducted in Sections 3 and 4 to evaluate and validate the accuracy and real-time performance of the proposed method.
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