• Acta Optica Sinica
  • Vol. 37, Issue 8, 0810001 (2017)
Yiquan Wu1、2、3、4、5、6、* and Zhilai Wang1
Author Affiliations
  • 1 College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China
  • 2 Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210044, China;
  • 3 Zhejiang Province Key Laboratory for Signal Processing, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
  • 4 Guangxi Key Lab of Multi-Source Information Mining and Security, Institute of Mineral Resources, Guangxi Normal University, Guilin, Guangxi 541004, China
  • 5 Key Laboratory of Geo-Spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu, Sichuan 610059, China
  • 6 Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, Ministry of Land and Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
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    DOI: 10.3788/AOS201737.0810001 Cite this Article Set citation alerts
    Yiquan Wu, Zhilai Wang. Infrared and Visible Image Fusion Based on Target Extraction and Guided Filtering Enhancement[J]. Acta Optica Sinica, 2017, 37(8): 0810001 Copy Citation Text show less
    Segmentation result based on two-dimensional Tsallis gray entropy
    Fig. 1. Segmentation result based on two-dimensional Tsallis gray entropy
    Schematic of accurate target extraction. (a) Threshold segmentation result of significant map; (b) final extracted target region
    Fig. 2. Schematic of accurate target extraction. (a) Threshold segmentation result of significant map; (b) final extracted target region
    Flow chart of the proposed fusion method
    Fig. 3. Flow chart of the proposed fusion method
    Three groups of visible images and infrared images. (a) Visible image of group 1; (b) infrared image of group 1; (c) visible image of group 2; (d) infrared image of group 2; (e) visible image of group 3; (f) infrared image of group 3
    Fig. 4. Three groups of visible images and infrared images. (a) Visible image of group 1; (b) infrared image of group 1; (c) visible image of group 2; (d) infrared image of group 2; (e) visible image of group 3; (f) infrared image of group 3
    Targets extracted from two infrared images by the proposed method and the method in Ref. [13]. (a) Targets extracted from the Fig. 4(b) by the proposed method; (b) targets extracted from the Fig. 4(d) by the proposed method; (c) targets extracted from the Fig. 4(f) by the proposed method; (d) targets extracted from the Fig. 4(b) by the method in Ref. [13]; (e) targets extracted from the Fig. 4(d) by the method in Ref. [13] ; (f) targets extracted from the Fig. 4(f) by the method in Ref. [13]
    Fig. 5. Targets extracted from two infrared images by the proposed method and the method in Ref. [13]. (a) Targets extracted from the Fig. 4(b) by the proposed method; (b) targets extracted from the Fig. 4(d) by the proposed method; (c) targets extracted from the Fig. 4(f) by the proposed method; (d) targets extracted from the Fig. 4(b) by the method in Ref. [13]; (e) targets extracted from the Fig. 4(d) by the method in Ref. [13] ; (f) targets extracted from the Fig. 4(f) by the method in Ref. [13]
    Fusion results on the images of group 1. (a) LP method; (b) WT method; (c) SWT method;(d) NSCT method; (e) method in Ref. [13]; (f) proposed method
    Fig. 6. Fusion results on the images of group 1. (a) LP method; (b) WT method; (c) SWT method;(d) NSCT method; (e) method in Ref. [13]; (f) proposed method
    Fusion results on the images of group 2. (a) LP method; (b) WT method; (c) SWT method;(d) NSCT method; (e) method in Ref. [13]; (f) proposed method
    Fig. 7. Fusion results on the images of group 2. (a) LP method; (b) WT method; (c) SWT method;(d) NSCT method; (e) method in Ref. [13]; (f) proposed method
    Fusion results on the images of group 3. (a) LP method; (b) WT method; (c) SWT method; (d) NSCT method; (e) method in Ref. [13]; (f) proposed method
    Fig. 8. Fusion results on the images of group 3. (a) LP method; (b) WT method; (c) SWT method; (d) NSCT method; (e) method in Ref. [13]; (f) proposed method
    Image groupFusion methodInformation entropyAverage gradientCorrelation coefficientSpatial frequencyDistortion degreeMutual informationStandard deviation
    Images of group 1LP method6.49517.75740.752511.057719.420611.040126.5996
    WT method6.77087.84340.576311.036423.290911.722432.8766
    SWT method6.32076.16020.75738.630619.615710.607424.0802
    NSCT method6.76557.86620.716311.305119.915611.575131.0908
    Method in Ref. [13]7.31057.44420.932112.953420.062613.345345.4183
    Proposed method7.36878.91810.938313.38778.870212.792146.6459
    Images of group 2LP method6.05107.77960.76929.654135.85728.938216.4286
    WT method6.31907.85980.96179.60303.58319.461520.9288
    SWT method5.98786.98600.79748.530235.09708.930015.5457
    NSCT method6.12827.45560.73749.323336.13099.08379.5244
    Method in Ref. [13]6.30274.47410.98686.305233.437110.566623.0787
    Proposed method6.46067.65660.96379.51174.58289.676223.3445
    Images of group 3LP method7.123516.56070.942821.550161.516512.096641.1500
    WT method7.253917.45720.914822.456824.987012.709053.5894
    SWT method7.045614.03100.954017.697426.037611.789939.6084
    NSCT method7.179917.01190.943722.327824.258012.184543.4219
    Method in Ref. [13]7.264116.86100.957824.230816.904714.534354.0441
    Proposed method7.340413.57830.978818.189216.507212.567655.4027
    Table 1. Quantitative evaluation results of six image fusion methods
    Yiquan Wu, Zhilai Wang. Infrared and Visible Image Fusion Based on Target Extraction and Guided Filtering Enhancement[J]. Acta Optica Sinica, 2017, 37(8): 0810001
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