三维动态图像重构特征移动误差消除方法研究

A Movement Error Elimination Method of Three-Dimensional Dynamic Image Reconstruction Characteristics

三维动态图像重构过程中,目标物体的特征因发生移动而产生误差,从而降低了三维动态图像重构的精确性。传统的算法不能避免引起目标物体特征移动误差的因素造成的影响。提出采用BP神经网络的三维动态图像重构中的特征移动误差消除方法。利用BP神经网络建立特征移动误差消除模型,对模型中的参数进行训练,利用最速下降学习法可以对模型中各层之间的连接权值进行学习,并反向调节,利用姿态因子对各层的连接权值进行自适应调整,从而使模型的输出误差不断降低,从而降低了特征移动误差。仿真结果表明,利用改进算法能够对三维动态图像重构中的特征移动误差进行消除,提高了三维动态图像重构的精度。

A movement error elimination method of three dimensional dynamic features in the image reconstruction is put forward based on BP neural network. A moving error elimination model is established, the parameters in the model are trained through BP neural network, the connection weights between layers are learned by using the steepest descent method and adaptively adjusted with the gesture factor, so that the output error of the model is descresed, thus the movement error of characteristics is reduced. Simulation results show that the improved algorithm can elimi- nate the error effectively, efficiency.