改进BP网络在超光谱图像压缩中的应用

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

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。

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.