Combined Noise Reduction in CT-Image Based on Adaptive Median Filter and Wavelet Packet

2011 ◽  
pp. 550-557
Author(s):  
Houjie Li ◽  
Jiyin Zhao ◽  
Shuang Xu ◽  
Yanqiu Cui
Keyword(s):  
Noise Reduction ◽  
Wavelet Packet ◽  
Median Filter ◽  
Ct Image ◽  
Adaptive Median Filter

Speckle Noise Reduction in SAR Imagery Using a Local Adaptive Median Filter

2004 ◽  
Vol 41 (3) ◽  
pp. 244-266 ◽  
Author(s):  
Fang Qiu ◽  
Judith Berglund ◽  
John R. Jensen ◽  
Pathik Thakkar ◽  
Dianwei Ren
Keyword(s):  
Noise Reduction ◽  
Median Filter ◽  
Speckle Noise ◽  
Adaptive Median Filter ◽  
Sar Imagery ◽  
Speckle Noise Reduction

CT image artifacts from brachytherapy seed implants: A postprocessing 3D adaptive median filter

2011 ◽  
Vol 38 (2) ◽  
pp. 712-718 ◽  
Author(s):  
Parminder S. Basran ◽  
Andrew Robertson ◽  
Derek Wells
Keyword(s):  
Median Filter ◽  
Image Artifacts ◽  
Ct Image ◽  
Adaptive Median Filter

Application of Improved Back Propagation Neural Network for the Recognition of Composite Insulator Hydrophobicity Grade

2013 ◽  
Vol 373-375 ◽  
pp. 1155-1158
Author(s):  
Kang Yan ◽  
Zhong Yuan Zhang
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Median Filter ◽  
Back Propagation ◽  
Histogram Equalization ◽  
Back Propagation Neural Network ◽  
Threshold Method ◽  
Safe Operation ◽  
Composite Insulator ◽  
Adaptive Median Filter

The detection of hydrophobicity is an important way to evaluate the performance of composite insulator, which is helpful to the safe operation of composite insulator. In this paper, the image processing technology and Back Propagation neural network is introduced to recognize the composite insulator hydrophobicity grade. First, hydrophobic image is preprocessed by histogram equalization and adaptive median filter, then the image was segmented by Ostu threshold method, and four features associated with hydrophobicity are extracted. Finally, the improved Back Propagation neural network is adopted to recognize composite insulator hydrophobicity grade. The experimental results show that the improved Back Propagation neural network can accurately recognize the composite insulator hydrophobicity

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