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Denoising
本文介绍了局部放电信号的消噪方法，主要基于改进的小波消噪和序列脉冲分析手段来实现。(This paper presents a de-noising method for partial discharge (PD) online monitoring of transformers. The method is based on an improved
wavelet de-noising approach and a pulse-sequence analysis method.)
- 2012-03-16 11:07:59下载
- 积分：1
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Untitled
自己编写离散小波变换与离散小波反变换程序对一幅图像做2级小波分解（离散小波变换）与合成（离散小波反变换）(Write your own discrete wavelet transform and discrete wavelet inverse transform procedure on an image to do two wavelet transform (DWT) and synthesis (discrete wavelet inverse transform))
- 2010-06-06 15:33:00下载
- 积分：1
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stran
说明： 基本的S变换matlab实现 用于时频分析 为初学者提供基本代码(S transformation for time-frequency analysis to provide basic code for beginners)
- 2021-01-13 16:38:48下载
- 积分：1
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GaborFilter
说明： 利用Gabor滤波器提取图像纹理特征，用于图像分类模式识别(Extract the texture feature using Gabor filter/wavelet. You should first generate cell array G, which is a set of kernels in freq domain, then pass G and the image to the function GABORCONV.)
- 2011-04-10 15:58:05下载
- 积分：1
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FK_Transform 实现f-k变换
说明： 实现f-k变换，功能强大，各种滤波处理，地震波等都能用(wavelet transformF -k transform, powerful, a variety of filtering, seismic waves can be used)
- 2019-03-20 15:44:28下载
- 积分：1
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roadidentity
说明： 主要针对道路提取程序，使用二值法和形态法(Road extraction procedures, using binary and morphological methods)
- 2019-12-14 19:47:51下载
- 积分：1
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Wavelet
小波包变换分析信号的MATLAB程序，可用于提取故障特征向量(Wavelet packet transform analysis of signals in MATLAB procedures, can be used to extract fault feature vector)
- 2020-07-01 05:40:01下载
- 积分：1
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wavelet-watermark
this watermarking is implemented using wavelet transform..
- 2012-01-02 20:31:13下载
- 积分：1
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xiaobo
关于小波变换的降噪处理，包括强制降噪，给定阈值降噪，默认阈值降噪等，并给出了对比图(Noise reduction processing on the wavelet transform, including mandatory noise reduction, noise reduction given threshold, default threshold noise reduction, and gives comparison chart)
- 2021-05-14 11:30:03下载
- 积分：1
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BCS-SPL-1.5-new
Block-based random image sampling is coupled with a projectiondriven
compressed-sensing recovery that encourages sparsity in
the domain of directional transforms simultaneously with a smooth
reconstructed image. Both contourlets as well as complex-valued
dual-tree wavelets are considered for their highly directional representation,
while bivariate shrinkage is adapted to their multiscale
decomposition structure to provide the requisite sparsity constraint.
Smoothing is achieved via a Wiener filter incorporated
into iterative projected Landweber compressed-sensing recovery,
yielding fast reconstruction. The proposed approach yields images
with quality that matches or exceeds that produced by a popular,
yet computationally expensive, technique which minimizes total
variation. Additionally, reconstruction quality is substantially
superior to that from several prominent pursuits-based algorithms
that do not include any smoothing
- 2020-11-23 19:29:34下载
- 积分：1
