Description: 小波方法和偏微分方程方法是图像去噪中的主要方法。该文提出基于离散小波变换对图像进行阈值去噪，得出了小波阈值的偏微
分方程表示形式，在此基础上研究偏微分方程的解法，采用分数步的小波阈值方法对图像去噪，得到了较好的去噪效果，同时可以保护边
缘。数值试验结果表明，该方法具有比小波方法更好的去噪效果，能获得较高的信噪比-Wavelet method and partial differential equations is the main method of image denoising. In this paper, based on discrete wavelet transform image threshold denoising, wavelet threshold obtained indicated that the form of partial differential equations, in this study based on the solution of partial differential equations, using fractional steps of wavelet thresholding methods for image to noise, have been well de-noising effect at the same time can protect the edge. Numerical experimental results show that the method is better than the wavelet method for denoising results are able to obtain a higher signal to noise ratio Platform: |
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Author:MaxineChan |
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Description: MATLAB下小波变换的原理教程及示例 包括：一维线性非线性近似、二维线性非线性近似、使用线性滤波过滤噪声、使用小波门限消除噪声、使用小波变换压缩一维信号、二维小波图像压缩等等。-MATLAB wavelet transform under the principle of tutorials and examples include: one-dimensional linear non-linear approximation, two-dimensional linear non-linear approximation, using linear filtering, filtering noise, and the use of wavelet thresholding to eliminate noise, the use of one-dimensional wavelet compression signal, two-dimensional wavelet image compression and so on. Platform: |
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Author:lym |
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Description: 将小波相邻系数相关性的降噪思想引入到冗余第2代小波中，提出了基于邻域相关性的冗余第2代小波降噪方法，该方法克服了传统阈值降噪没有考虑小波系数之间相关性的不足。-Aiming at fault feature extraction in the background of strong noise, a wavelet denoising idea by incorporating neighboring coefficients is introduced into redundant second generation wavelet case. A denoising method of redundant second generation wavelet using neighbor dependency is presented. It overcomes the deficiency of traditional thresholding approaches. In this method, an original signal is decomposed by redundant second generation wavelet, and the detail and approximation signals have the same length as the original signal. The detail signals at each scale are then processed by neighbor dependency. Finally, the approximation signal and processed detail signals are reconstructed by inverse transform of redundant second generation wavelet to realize the signal denoising. Platform: |
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Author:杨飞宇 |
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Description: 对设备进行故障诊断的主要方法就是测量故障
设备的振动或噪声, 并对其进行分析, 从而找出故障原因。然而振动或噪声信号中除了对分析故障有用的信息外, 还有大量的噪声成分。只有有效地滤除噪声, 才能获得有用的信息, 从而得到可靠的分析结论。传统的滤噪方法是将被噪声污染的信号通过一个滤波器, 滤掉噪声频率成分。但对于短时瞬态信号、非平稳信号、含宽带噪声的信号, 采用传统处理方法有着明显的局限性。小波变换为信号去噪提供了一种有效的方法, 小波阈值去噪具有传统方法不可比拟的优越性。但是小波分解的频域重叠性和阈值选取的不确定性, 使得小波阈值去噪法有也不能得到理想效果。-Equipment fault diagnosis method is to measure the fault
Equipment vibration or noise, and its analysis in order to identify the cause of the malfunction. Vibration or noise signals, however, in addition to the analyze fault useful information, there is a lot of noise components. Only effectively filter out the noise in order to obtain useful information, to obtain reliable conclusions. Traditional filtering method based noise pollution signal through a filter to filter out the noise frequency components. But for the short-term transient signal, non-stationary signals, including broadband noise signal, using the traditional approach has obvious limitations. The wavelet transform provides an effective method for signal de-noising, wavelet thresholding has incomparable superiority of traditional methods. Wavelet frequency domain overlap threshold uncertainty, the wavelet thresholding method can not get the desired effect. Platform: |
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Author:哈哈 |
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Search - thresholding using wavelet transform