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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    An image compression model based on the FA-LMBP hybrid neural network algorithm is proposed by the combination of the firefly algorithm and LM (Levenberg-Marquardt) algorithm. First, a set of optimal approximate solutions of the backpropagation(BP)network weight threshold are obtained by the global search of the target function based on the firefly algorithm, then the approximate solution is used as the initial value of the BP model, and the LM algorithm is used to carry out the secondary optimization training for these weight thresholds, thereby obtaining the final image compression model. The experimental results show that the reconstruction quality of the compression image model based on the FA-LMBP hybrid neural network algorithm is obviously higher than that of the basic BP model and the LMBP model under the same training times and error accuracy.

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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: Wang Haijun (wanghaijun11249@126.com)

    DOI:10.3788/LOP56.191005

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