• Laser & Optoelectronics Progress
  • Vol. 60, Issue 16, 1628006 (2023)
Hongkai Wu1,2,*, Keyan Dong2,**, Yansong Song2, Xiaona Dong2, and Ming Yuan2
Author Affiliations
  • 1College of Opto-Electronic Engineering, Changchun University of Technology, Changchun 130022, Jilin, China
  • 2Institute of Space Photoelectric Technology, Changchun University of Science and Technology, Changchun 130022, Jilin, China
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    DOI: 10.3788/LOP222118 Cite this Article Set citation alerts
    Hongkai Wu, Keyan Dong, Yansong Song, Xiaona Dong, Ming Yuan. Infrared Small Target Detection Method Based on Weighted Patch Contrast[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1628006 Copy Citation Text show less
    Sliding window with 9 subblocks
    Fig. 1. Sliding window with 9 subblocks
    Sliding window passing through the interfering object
    Fig. 2. Sliding window passing through the interfering object
    Infrared images of four different scenes. (a) Ground background; (b) forest building background; (c) cloud background; (d) ocean sky background
    Fig. 3. Infrared images of four different scenes. (a) Ground background; (b) forest building background; (c) cloud background; (d) ocean sky background
    Saliency maps correspending to infrared images in Fig.3. (a) Ground background; (b) forest building background; (c) cloud background; (d) ocean sky background
    Fig. 4. Saliency maps correspending to infrared images in Fig.3. (a) Ground background; (b) forest building background; (c) cloud background; (d) ocean sky background
    Experimental results of response maps. (a) Original infrared images; (b) original gray maps; (c) gray responsemaps using LMWIE;(d) gray response maps using MPCM; (e) gray response maps using proposed method
    Fig. 5. Experimental results of response maps. (a) Original infrared images; (b) original gray maps; (c) gray responsemaps using LMWIE;(d) gray response maps using MPCM; (e) gray response maps using proposed method
    Detection results of three algorithms under ground background. (a) Proposed algorithm; (b) LCM algorithm; (c) MPCM algorithm
    Fig. 6. Detection results of three algorithms under ground background. (a) Proposed algorithm; (b) LCM algorithm; (c) MPCM algorithm
    The difference between the means under two algorithms. (a) Original image; (b) the mean difference value of the center block and the neighborhood block; (c) the value of the advanced weighted entropy
    Fig. 7. The difference between the means under two algorithms. (a) Original image; (b) the mean difference value of the center block and the neighborhood block; (c) the value of the advanced weighted entropy
    AlgorithmGroundForests and buildingsClouds
    RSCRFBSFRSCRFBSFRSCRFBSF
    MPCM7.69768.743413.29833.092027.51987.5009
    LMWIE6.42592.85007.76764.51722.52761.7312
    Proposed algorithm24.439015.807773.431216.9586inf15.0567
    Table 1. RSCR and FBSF of three different scenes
    AlgorithmGroundForests and buildingsClouds
    LCM0.375000.1304
    MPCM0.19270.20400.1972
    LMWIE0.13040.047620.0909
    Proposed algorithm0.090900
    Table 2. Probability of false alarm of three different scenes
    Hongkai Wu, Keyan Dong, Yansong Song, Xiaona Dong, Ming Yuan. Infrared Small Target Detection Method Based on Weighted Patch Contrast[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1628006
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