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兰州理工大学 [3]
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Noise reduction of a safety valve pressure relief signal based on an improved wavelet threshold function
期刊论文
Zhendong yu Chongji/Journal of Vibration and Shock, 2021, 卷号: 40, 期号: 12, 页码: 143-150
作者:
Li, Shuxun
;
Wang, Zhihui
;
Kang, Yunxing
;
Hou, Jianjun
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浏览/下载:10/0
  |  
提交时间:2022/02/17
Butterworth filters
Exponential functions
Safety valves
Wavelet decomposition
Adaptive wavelet thresholds
Adjustment factors
Attenuation characteristics
Mechanical systems
Noise reduction effect
Noise reduction methods
Simulated signals
Threshold functions
An adaptive wavelet shrinkage de-noising algorithm for low altitude flying acoustic targets
期刊论文
Zhendong yu Chongji/Journal of Vibration and Shock, 2017, 卷号: 36, 期号: 9, 页码: 153-158 and 230
作者:
Li, Suoping
;
Zhou, Yong
;
Zhou, Yongqiang
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  |  
浏览/下载:4/0
  |  
提交时间:2020/11/14
Acoustic noise
Shrinkage
Signal processing
Wavelet decomposition
Acoustic targets
Adaptive wavelet thresholds
De-noising
De-noising algorithm
Optimal decomposition
Signal information
Threshold de-noising
Threshold functions
FDCT on the edge of the image detail enhancement improvement
会议论文
Changsha, China, April 18, 2014 - April 20, 2014
作者:
Zhang, Yong
;
Qian, Yan
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  |  
浏览/下载:11/0
  |  
提交时间:2020/11/15
Intelligent systems
Adaptive threshold method
Adaptive thresholds
Cyclic shifts
Fast discrete curvelet transform (FDCT)
FDCT
Information preservations
Peak signal-to-noise ratio
USFFT and wrap
自适应小波阈值语音增强新方法
期刊论文
2010, 2010
马晓红
;
宋辉
;
殷福亮
;
MA Xiao-hong
;
SONG hui
;
YIN Fu-liang
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  |  
浏览/下载:3/0
Destriping method using lifting wavelet transform of remote sensing image (EI CONFERENCE)
会议论文
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
Zhao B.
;
He B.
;
Cong Y.
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浏览/下载:22/0
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提交时间:2013/03/25
Based on the characteristic of striping noise in remote sensing images
a new destriping noise technique for the improved multi-threshold method using lifting wavelet transform applied to remote sensing imagery is presented in this letter. Have used the lifting wavelet decomposition algorithm
the thresholds are determined by corresponding wavelet coefficients in every scale. Remote sensing imagery is so large that the algorithm must be fast and effective. The lifting wavelet transform is easily realized and inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the method with some traditional destriping methods both by visual inspection and by appropriate indexes of quality of the denoised images. From the comparison we can see that the adaptive threshold method can preserve the spectral characteristic of the images while effectively remove striping noise and it did better than the existed ones. 2010 IEEE.
Image denoising and enhancement based on adaptive wavelet thresholding and mathematical morphology
会议论文
作者:
Zhang, Yungang
;
Zhang, Bailing
;
Lu, Wenjin
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浏览/下载:3/0
  |  
提交时间:2019/12/18
Adaptive thresholding
Adaptive thresholds
Adaptive wavelet thresholding
Image denoising and enhancements
Morphological operations
PSNR (peak signal to noise ratio)
Wavelet shrinkage
Wavelet thresholding
小波变换在低场脉冲核磁共振信号降噪中的应用
学位论文
博士: 中国科学院电工研究所, 2007
1郑传行,电工研究所
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浏览/下载:9/0
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提交时间:2010/10/18
核磁共振
噪声
信号处理
小波变换
降噪 NMR
noise
signal processing
wavelet transform
denoising
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