Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (15): 15-23.DOI: 10.3778/j.issn.1002-8331.2003-0294

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Survey of Image Compression Algorithm Based on Deep Learning

YU Heng, MEI Hongyan, XU Xiaoming, JIA Huiping   

  1. School of Electronics and Information Engineering, Liaoning University of Technology, Jinzhou, Liaoning 121001, China
  • Online:2020-08-01 Published:2020-07-30



  1. 辽宁工业大学 电子与信息工程学院,辽宁 锦州 121001


With the continuous development of deep learning and the explosive growth of image data, how to use deep learning to obtain higher compression ratio and higher quality images has gradually become one of the hot research issues. Through the analysis of the related literatures in recent years, the image compression method based on the deep learning is summarized and analyzed according to the Convolutional Neural Network(CNN), Recurrent Neural Network(RNN), Generative Adversarial Network(GAN). This paper enumerates the typical examples, and the image compression algorithm based on depth study of the training data set, commonly used evaluation indexes are introduced, according to the deep learning advantages in the field of image compression for its future development trend are summarized and discussed.

Key words: deep learning, image compression, Convolutional Neural Network(CNN), Recurrent Neural Network(RNN), Generative Adversarial Network(GAN)



关键词: 深度学习, 图像压缩, 卷积神经网络, 循环神经网络, 生成对抗网络