基于新型二层误差逆传播网络的图像压缩

基于误差逆传播算法对图像进行压缩的工作已有很多，怛存在着人工神经网络训练时间较长，精度偏低等问题。考虑到利用三层及三层以上BP网络对图像压缩，其有效信息是中间层单元上的输出值和中间层与输出层之间的连接权，而输入层与中间层的连接权是冗余的，以至于对学习速度和压缩质量有负面影响。基于此我们提出了新型二层误差逆传播网络拓扑结构和算法。经过上机压缩测试，相对于三层BP网络、三层以上BP网络以及嵌套BP网络图像压缩的压缩比、学习速度和压缩质量都有很大提高，取得了很好的效果。

IMAGE COMPRESSION BASED UPON NEW BACK PROPAGATION

There has been many techniques of image compression based upon back propagation algorithm,but they all have their own limits,the long study speed and lower compression quality.In the process of image compression,considering that the three or more layers BP networks have some redundancies in the weights between input layer and meddle layer so as to effect the network's study speed and compression quality,we bring forward a new two layers back propagation networks and it's algorithm.It has been proved in many examples that the new networks get a good result in the compression rate,study speed and compression quality of image compression than other back propagations.