Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (4): 1467-1473.doi: 10.13229/j.cnki.jdxbgxb.20230730

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Fast star point extraction with improved run-length encoding algorithm

Jia-bao ZHANG(),Jian-yang ZHANG,He LIU,Yan LI   

  1. College of Instrumentation and Electrical Engineering,Jilin University,Changchun 130061,China
  • Received:2023-07-12 Online:2025-04-01 Published:2025-06-19

Abstract:

To enhance the real-time performance and accuracy of star point centroid extraction, an improved run-length encoding algorithm based on field programmable gate array(FPGA) was proposed for fast star point extraction. The algorithm combines the characteristics of star point targets with the parallel processing structure of field programmable gate array, addressing the shortcomings of the traditional run-length encoding algorithm that requires setting equivalence tables for label merging and multiple rounds of polling for run-length encoding during extraction. It only requires scanning the image once, and after a delay of several clock cycles, the centroid coordinate of the star point can be extracted. Finally, the algorithm is tested and validated on an field programmable gate array of a star sensor. With a clock frequency of 50 MHz and an input image resolution of 1 280×1 024 pixels, the algorithm takes about 2 us to extract the centroid of the star point, and the position is completely accurate. Compared to the nearly 19 ms consumed by centroid extraction using an Advanced RISC Machine(ARM), the improved algorithm demonstrates significant advantages and holds notable engineering application value.

Key words: signal and information processing, centroid extraction, field programmable gate array (FPGA), connected domain scan, star sensor, run-length encoding

CLC Number: 

  • V448.22

Fig.1

Connected area determines the status"

Fig.2

Primordial star points and distorted star points"

Fig.3

Distortion star label merging and recovery diagram"

Fig.4

Anomalous star target"

Fig.5

Flow chart of proposed algorithm"

Table 1

FPGA resource usage"

4LUTDFFRAM1K18User I/O
Used1 017(1.18%)555(0.64%)2(1.83%)41(15.36%)

Table 2

Extraction results of 5 star points in simulated star map"

目标

序号

MATLAB提取质心坐标/像素本算法提取质心坐标/像素

FPGA中质心

提取时间/μs

ARM中质心

提取时间/μs

XYXY
11 053.760 41645.715 4601 053.760 41645.715 4600.616 464
2920.490 788224.004 605920.490 788224.004 605
31 010.325 242364.962 7831 010.325 242364.962 783
4602.477 215761.500 000602.477 215761.500 000
5530.214 577983.606 267530.214 577983.606 267

Table 3

Comparison results of 10 and 15 star points existing in simulated star map"

星点个数对比结果

FPGA中质心

提取时间/μs

ARM中质心

提取时间/μs

10完全一致1.017 544
15完全一致1.418 624

Fig.6

Simulation data"

Fig.7

Simulated star map(reverse color processing)"

Fig.8

Simulate special star maps(reverse color processing)"

Fig.9

Actual shot test"

Table 4

Special star map star extraction results"

目标序号

MATLAB提取

质心坐标/像素

本文算法提取

质心坐标/像素

XYXY
1367.919 469409.935 398367.919 469409.935 398
2470.379 032537.242 943470.379 032537.242 943
3393.917 574543.201 525393.917 574543.201 525
4217.110 975613.310 975217.110 975613.310 975
5676.900 000671.700 000676.900 000671.700 000
6188.531 914701.067 375188.531 914701.067 375
7642.077 777824.655 555642.077 777824.655 555
8231.578 651862.460 674231.578 651862.460 674
971.000 00060.200 000071.000 00060.200 000
10552.000 000173.357 142552.000 000173.357 142
11166.000 000755.500 000异常星点目标
12656.000 000400.500 000异常星点目标
13687.769 328635.372 269异常星点目标

Fig.10

Field stargazing experiment"

Table 5

Extraction of star points from field observation"

目标

序号

MATLAB提取

质心坐标/像素

本文算法提取

质心坐标/像素

XYXY
1510.000 000517.500 000异常星点目标
2530.500 000395.000 000异常星点目标
3736.535 874439.867 713736.535 874439.867 713
4970.006 906104.754 143970.006 906104.754 143
51 097.141 509172.858 4901 097.141 509172.858 490
61 245.315 420380.996 4951 245.315 420380.996 495
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