• Laser & Optoelectronics Progress
  • Vol. 56, Issue 9, 091006 (2019)
Hongpu Liu1、2、3, Mengjing Zheng1、3, Xiangdan Hou1、3、*, Bocen Li1、3, and Jiazhuo Du1、3
Author Affiliations
  • 1 School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China
  • 2 School of Electrical Engineering, Hebei University of Technology, Tianjin 300401, China
  • 3 Hebei Provincial Key Laboratory of Big Data Computing, Tianjin 300401, China
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    DOI: 10.3788/LOP56.091006 Cite this Article Set citation alerts
    Hongpu Liu, Mengjing Zheng, Xiangdan Hou, Bocen Li, Jiazhuo Du. Enhancement Algorithm of Fractional Differential Medical Images Based on Local Binary Pattern Variance[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091006 Copy Citation Text show less
    LBP mode
    Fig. 1. LBP mode
    Circular neighborhood system
    Fig. 2. Circular neighborhood system
    Diagram of unified LBP mode when P=8
    Fig. 3. Diagram of unified LBP mode when P=8
    Mode and mode frequency map of textured image
    Fig. 4. Mode and mode frequency map of textured image
    Angle and mode frequency map of textured image
    Fig. 5. Angle and mode frequency map of textured image
    Eight directions of LBPV
    Fig. 6. Eight directions of LBPV
    Fractional masks for eight directions. (a) 0°; (b) 45°; (c) 90°; (d) 135°; (e) 180°; (f) 225°; (g) 270°; (h) 315°
    Fig. 7. Fractional masks for eight directions. (a) 0°; (b) 45°; (c) 90°; (d) 135°; (e) 180°; (f) 225°; (g) 270°; (h) 315°
    Original images and enhanced images. (a) Original images; (b) enhanced images of Fig. 8(a); (c) original images; (d) enhanced images of Fig. 8(c)
    Fig. 8. Original images and enhanced images. (a) Original images; (b) enhanced images of Fig. 8(a); (c) original images; (d) enhanced images of Fig. 8(c)
    Enhanced images of humeral head and its local images with different methods. (a) Original images; (b) method in Ref. [5]; (c) method in Ref. [6]; (d) method in Ref. [9]; (e) proposed method
    Fig. 9. Enhanced images of humeral head and its local images with different methods. (a) Original images; (b) method in Ref. [5]; (c) method in Ref. [6]; (d) method in Ref. [9]; (e) proposed method
    Enhanced images of tibia and its local images with different methods. (a) Original images; (b) method in Ref. [5]; (c) method in Ref. [6]; (d) method in Ref. [9]; (e) proposed method
    Fig. 10. Enhanced images of tibia and its local images with different methods. (a) Original images; (b) method in Ref. [5]; (c) method in Ref. [6]; (d) method in Ref. [9]; (e) proposed method
    ImageAGEImageAGE
    Fig. 8(a1)6.685.75Fig. 8(a3)4.755.42
    Fig. 8(b1)10.926.24Fig. 8(b3)8.756.00
    Fig. 8(c1)4.415.65Fig. 8(c3)3.034.44
    Fig. 8(d1)7.425.95Fig. 8(d3)5.485.09
    Fig. 8(a2)5.064.82Fig. 8(a4)4.795.47
    Fig. 8(b2)9.535.70Fig. 8(b4)8.345.88
    Fig. 8(c2)3.325.27Fig. 8(c4)2.984.27
    Fig. 8(d2)5.555.61Fig. 8(d4)5.714.99
    Table 1. Evaluation parameters of each image in Fig. 8
    ImageAGE
    Fig. 9(a)7.374.97
    Fig. 9(b)11.835.14
    Fig. 9(c)8.364.98
    Fig. 9(d)17.415.27
    Fig. 9(e)12.005.33
    Table 2. Evaluation parameters of each image in Fig. 9
    ImageAGE
    Fig. 10(a)8.834.52
    Fig. 10(b)11.234.57
    Fig. 10(c)9.004.42
    Fig. 10(d)14.094.63
    Fig. 10(e)11.614.80
    Table 3. Evaluation parameters of each image in Fig. 10
    Hongpu Liu, Mengjing Zheng, Xiangdan Hou, Bocen Li, Jiazhuo Du. Enhancement Algorithm of Fractional Differential Medical Images Based on Local Binary Pattern Variance[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091006
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