From the course: Wavelet Analysis: Applications with Wolfram Language
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Denoising Images - Wolfram Language Tutorial
From the course: Wavelet Analysis: Applications with Wolfram Language
Denoising Images
So keeping with the theme of image processing, let us now look at how you can use wavelet analysis to denoise images. So we're going to use examples as before in order to bring this point across. So we're going to make use of this picture of an astronaut. And we are going to apply a certain amount of noise onto this image so that it becomes a grainy image. Now we are going to perform a discrete wavelet transform on this grainy image. Before we do further analysis, it's important to have a look at how the image looks like, and this is what the image looks like. It's got some colored noise to it. Now in order to get rid of the noise, we are going to perform thresholding. So we have done the DiscreteWaveletTransform. We apply a wavelet threshold. In this case, we are using the soft method, and we are going to make use of an algorithm associated with the SURE method. And we are going to apply the threshold on certain coefficients. And we are going to evaluate that. And now when you invert…
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