A Novel FPGA-Based Architecture for Fast Automatic Target Detection in Hyperspectral Images
AbstractOnboard target detection of hyperspectral imagery (HSI), considered as a significant remote sensing application, has gained increasing attention in the latest years. It usually requires processing huge volumes of HSI data in real-time under constraints of low computational complexity and high detection accuracy. Automatic target generation process based on an orthogonal subspace projector (ATGP-OSP) is a well-known automatic target detection algorithm, which is widely used owing to its competitive performance. However, ATGP-OSP has an issue to be deployed onboard in real-time target detection due to its iteratively calculating the inversion of growing matrices and increasing matrix multiplications. To resolve this dilemma, we propose a novel fast implementation of ATGP (Fast-ATGP) while maintaining target detection accuracy of ATGP-OSP. Fast-ATGP takes advantage of simple regular matrix add/multiply operations instead of increasingly complicated matrix inversions to update growing orthogonal projection operator matrices. Furthermore, the updated orthogonal projection operator matrix is replaced by a normalized vector to perform the inner-product operations with each pixel for finding a target per iteration. With these two major optimizations, the computational complexity of ATGP-OSP is substantially reduced. What is more, an FPGA-based implementation of the proposed Fast-ATGP using high-level synthesis (HLS) is developed. Specifically, an efficient architecture containing a bunch of pipelines being executed in parallel is further designed and evaluated on a Xilinx XC7VX690T FPGA. The experimental results demonstrate that our proposed FPGA-based Fast-ATGP is able to automatically detect multiple targets on a commonly used dataset (AVIRIS Cuprite Data) at a high-speed rate of 200 MHz with a significant speedup of nearly 34.3 times that of ATGP-OSP, while retaining nearly the same high detection accuracy. View Full-Text
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Lei, J.; Wu, L.; Li, Y.; Xie, W.; Chang, C.-I.; Zhang, J.; Huang, B. A Novel FPGA-Based Architecture for Fast Automatic Target Detection in Hyperspectral Images. Remote Sens. 2019, 11, 146.
Lei J, Wu L, Li Y, Xie W, Chang C-I, Zhang J, Huang B. A Novel FPGA-Based Architecture for Fast Automatic Target Detection in Hyperspectral Images. Remote Sensing. 2019; 11(2):146.Chicago/Turabian Style
Lei, Jie; Wu, Lingyun; Li, Yunsong; Xie, Weiying; Chang, Chein-I; Zhang, Jintao; Huang, Biying. 2019. "A Novel FPGA-Based Architecture for Fast Automatic Target Detection in Hyperspectral Images." Remote Sens. 11, no. 2: 146.
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