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Laser & Optoelectronics Progress, Volume. 56, Issue 19, 191005(2019)

Application of FA-LMBP Hybird Neural Network Algorithm in Image Compression

Haijun Wang1、*, Tao Jin1, and Ke Neimule Men2
Author Affiliations
  • 1Department of Mathematics and Computer Engineering, Ordos Institute of Technology, Ordos, Inner Mongolia 0 17000, China
  • 2Department of Information Engineering, Ordos Institute of Technology, Ordos, Inner Mongolia 0 17000, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
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    References (16)
    Cited By (2)
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    Figures & Tables(11)
    Basic BP algorithm training curve

    Fig. 1. Basic BP algorithm training curve

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    LMBP algorithm training curve

    Fig. 2. LMBP algorithm training curve

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    FA-LMBP algorithm flow

    Fig. 3. FA-LMBP algorithm flow

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    Data matrix of 128 pixel×128 pixel Lena original image

    Fig. 4. Data matrix of 128 pixel×128 pixel Lena original image

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    Normalized partial sample matrix

    Fig. 5. Normalized partial sample matrix

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    BP model structure used in compression model

    Fig. 6. BP model structure used in compression model

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    Comparison of decompression and reconstruction effects of different BP algorithms for Lena training images when K=2. (a) Original image; (b) BP reconstruction image; (c) LMBP reconstruction image; (d) FA-LMBP reconstruction image

    Fig. 7. Comparison of decompression and reconstruction effects of different BP algorithms for Lena training images when K=2. (a) Original image; (b) BP reconstruction image; (c) LMBP reconstruction image; (d) FA-LMBP reconstruction image

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    Comparison of decompression and reconstruction effects of different BP algorithms for Cameraman testing images when K=2. (a) Original image; (b) BP reconstruction image; (c) LMBP reconstruction image; (d) FA-LMBP reconstruction image

    Fig. 8. Comparison of decompression and reconstruction effects of different BP algorithms for Cameraman testing images when K=2. (a) Original image; (b) BP reconstruction image; (c) LMBP reconstruction image; (d) FA-LMBP reconstruction image

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    Comparison of decompression and reconstruction effects of different BP algorithms for Brain testing images when K=2. (a) Original image; (b) BP reconstruction image; (c) LMBP reconstruction image; (d) FA-LMBP reconstruction image

    Fig. 9. Comparison of decompression and reconstruction effects of different BP algorithms for Brain testing images when K=2. (a) Original image; (b) BP reconstruction image; (c) LMBP reconstruction image; (d) FA-LMBP reconstruction image

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    • Table 1. Reconstruction image evaluation of compression models based on different algorithms when K=2

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      Table 1. Reconstruction image evaluation of compression models based on different algorithms when K=2

      AlgorithmLenaCameramanBrain
      PSNRSSIMPSNRSSIMPSNRSSIM
      BP10.15380.04239.37610.03567.08350.0243
      LMBP28.0590.863525.00340.756522.79340.7541
      FA-LMBP28.5290.882926.70530.806924.76110.8148

    • Table 2. Reconstruction image evaluation of compression models based on different algorithms when K=4

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      Table 2. Reconstruction image evaluation of compression models based on different algorithms when K=4

      AlgorithmLenaCameramanBrain
      PSNRSSIMPSNRSSIMPSNRSSIM
      BP9.85990.03739.17890.02617.15210.0208
      LMBP27.28780.862724.53020.768522.49390.711
      FA-LMBP27.36330.863825.45250.812423.32010.8193
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    Haijun Wang, Tao Jin, Ke Neimule Men. Application of FA-LMBP Hybird Neural Network Algorithm in Image Compression[J]. Laser & Optoelectronics Progress, 2019, 56(19): 191005

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    Paper Information

    Category: Image Processing

    Received: Feb. 27, 2019

    Accepted: Apr. 22, 2019

    Published Online: Oct. 12, 2019

    The Author Email: Haijun Wang (wanghaijun11249@126.com)

    DOI:10.3788/LOP56.191005

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology