• Acta Optica Sinica
  • Vol. 38, Issue 10, 1010006 (2018)
Aiping Yang*, Meiqi Zhao, Haixin Wang, and Liyu Lu
Author Affiliations
  • School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
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    DOI: 10.3788/AOS201838.1010006 Cite this Article Set citation alerts
    Aiping Yang, Meiqi Zhao, Haixin Wang, Liyu Lu. Nighttime Image Dehazing Based on Low-Pass Filtering and Joint Optimization of Multi-Feature[J]. Acta Optica Sinica, 2018, 38(10): 1010006 Copy Citation Text show less
    Flowchart of the proposed algorithm
    Fig. 1. Flowchart of the proposed algorithm
    Atmospheric light and dehazed results based on different methods. (a) Input image; (b) atmospheric light of Ref. [7] method; (c) dehazed result of Ref. [7] method; (d) atmospheric light of Ref. [14] method; (e) dehazed result of Ref. [14] method; (f) low-pass filtering of proposed method; (g) atmospheric light of proposed method; (h) dehazed result of proposed method
    Fig. 2. Atmospheric light and dehazed results based on different methods. (a) Input image; (b) atmospheric light of Ref. [7] method; (c) dehazed result of Ref. [7] method; (d) atmospheric light of Ref. [14] method; (e) dehazed result of Ref. [14] method; (f) low-pass filtering of proposed method; (g) atmospheric light of proposed method; (h) dehazed result of proposed method
    Mapping relationship between input image and output image
    Fig. 3. Mapping relationship between input image and output image
    Dehazed results based on different transmittances. (a) Input image; (b) t=0.1; (c) t=0.5; (d) t=0.9
    Fig. 4. Dehazed results based on different transmittances. (a) Input image; (b) t=0.1; (c) t=0.5; (d) t=0.9
    Estimation and optimization of transmittance. (a) Original image; (b) initial transmittance; (c) optimized transmittance; (d) dehazed image
    Fig. 5. Estimation and optimization of transmittance. (a) Original image; (b) initial transmittance; (c) optimized transmittance; (d) dehazed image
    Color correction of nighttime image by different methods. (a1)(a2) Original images; (b1)(b2) corrected images by Shade of Gray[20] method; (c1)(c2) corrected images by White balance[21] method; (d1)(d2)corrected images by proposed method
    Fig. 6. Color correction of nighttime image by different methods. (a1)(a2) Original images; (b1)(b2) corrected images by Shade of Gray[20] method; (c1)(c2) corrected images by White balance[21] method; (d1)(d2)corrected images by proposed method
    Dehazed results of different methods. (a1)(a2) Input nighttime images; (b1)(b2) results of Retinex method; (c1)(c2) results of histogram equalization method; (d1)(d2) results of proposed method
    Fig. 7. Dehazed results of different methods. (a1)(a2) Input nighttime images; (b1)(b2) results of Retinex method; (c1)(c2) results of histogram equalization method; (d1)(d2) results of proposed method
    Dehazed results of different methods for Pavilion. (a) Pavilion image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Fig. 8. Dehazed results of different methods for Pavilion. (a) Pavilion image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Dehazed resultsof different methods for Train. (a) Train image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Fig. 9. Dehazed resultsof different methods for Train. (a) Train image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Dehazed results of different methods for Building. (a) Building image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Fig. 10. Dehazed results of different methods for Building. (a) Building image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Dehazed results of different methods for Street. (a) Street image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    Fig. 11. Dehazed results of different methods for Street. (a) Street image; (b) result of Ref. [7] method; (c) result of Ref. [12] method; (d) result of Ref. [14] method; (e) result of proposed method
    ImageRef. [7] methodRef. [12] methodRef. [14] methodProposed method
    KCKCKCKC
    Pavilion1.3521.211.2919.421.4537.411.3241.98
    Train1.8820.231.7423.861.9349.521.7150.94
    Building2.6719.741.6121.231.7646.291.5051.86
    Street1.8416.241.0325.060.8229.890.7934.52
    Table 1. Comparison of K/C of different methods
    Aiping Yang, Meiqi Zhao, Haixin Wang, Liyu Lu. Nighttime Image Dehazing Based on Low-Pass Filtering and Joint Optimization of Multi-Feature[J]. Acta Optica Sinica, 2018, 38(10): 1010006
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