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改进BP 网络在超光谱图像压缩中的应用

  

  • 出版日期:2013-10-31 发布日期:2015-06-19

Application of Improved BP Neural Network in Hyper-spectral Image Compression

  • Online:2013-10-31 Published:2015-06-19

摘要: 鉴于超光谱图像的应用领域,对超光谱图像的压缩要重点考虑压缩质量和
压缩时间。将BP 神经网络用于超光谱图像压缩可得到较好的压缩质量。在保证较好恢复质
量的前提下,提出了一种利用Cauchy 误差估计器、在转移函数中引入陡度因子、进行导数
提升及各层调节变尺度的改进BP 算法进一步减少压缩时间。实验结果表明:算法减少了压
缩时间,提高了编码效率。

关键词: 图像压缩, 超光谱图像, 神经网络, BP 算法

Abstract: The hyper-spectral image compression is focused on compression quality and time
owing to the application fields of hyper-spectral image. The application of BP Neural Network in
the hyper-spectral image compression can get better compression quality. A joint-optimized
improved algorithm on the premise of good renewed qualities is presented. It uses Cauchy error
estimator and shape factor in Sigmoid function, upgrades the differential coefficient and each lay
adapts different step adjustment. Simulation results prove that the algorithm can reduce
compression time and improve coding efficiency.

Key words: image compression, hyper-spectral image, neural network, BP algorithm