Neural network decision directed edge-adaptive Kalman filter for image estimation

被引：7
|
作者：
Azimi-Sadjadi, MR [1 ]
Xiao, RR [1 ]
Yu, X [1 ]
机构：
[1] Colorado State Univ, Dept Elect Engn, Ft Collins, CO 80523 USA
来源：
IEEE TRANSACTIONS ON IMAGE PROCESSING | 1999年 / 8卷 / 04期
关键词：
image restoration; Kalman filtering; neural networks;
D O I：
10.1109/83.753746
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A neural network-based scheme for decision directed edge-adaptive Kalman filtering is introduced in this work. A backpropagation neural network makes the decisions about the orientation of the edges based on the information in a window centered at the current pixel being processed. Then based upon the neural network output an appropriate image model which closely matches the local statistics of the image is chosen for the Kalman filter. This prevents the oversmoothing of the edges, which would have otherwise been caused by the standard Kalman filter. Simulation results are presented which show the effectiveness of the proposed scheme.
引用
收藏
页码：589 / 592
页数：4
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