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Image denoising with wavelet
We first load an image, and add some noise to it
The orthogonal wavelet transform is not very efficient for image denoising because it lacks translation invariance. This is why there is so many reconstruction artifact
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Quincunx wavelet transforms
Quincunx wavelets are non-separable transform that allows to avoid using vertical/horizontal wavelets. The scaling grows like 2^{j/2} with the scale j instead of 2^j, which can be advantageous.
Biorthogonal quincunx w
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Function to plot the Region of convergence for Suprathreshold stochastic resonance+Translation invariant wavelet packet transform detector for transient signals. Hypotheses:
Ho : x[n] = w[n] i.e. signal absent
H1 : x[n] = s[n] + w[n] i.e. signal
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Function to plot the region of convergence for a stochastic resonance detector followed by a translation invariant wavelet packet transform detector for transient signals in shallow oceans.
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利用平移不变量发，实现小波阈值去噪，能够有效的消去伪吉布斯现象，利于后续的特征点提取。-The use of translation invariant issued to wavelet threshold denoising can effectively eliminate the Gibbs phenomenon, and conducive to the subsequent feature point extraction.
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基于平移不变量小波去噪的GUI程序，平移不变量小波去噪是阀值去噪的进一步改进，去除了信吉布斯现象-Translation invariant wavelet denoising based GUI program is translation invariant wavelet denoising threshold denoising further improvement, in addition to the letter Gibbs phenomenon
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利用平移不变量进行小波去噪，对信号的处理很好，值得你去看看。-The use of translation invariant wavelet denoising, signal processing is very good, worth a look.
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