Denoising Gabor Transforms
نویسندگان
چکیده
We describe denoising one-dimensional signals by thresholding Blackman windowed Gabor transforms. This method is compared with Gauss-windowed Gabor threshold denoising and wavelet-based denoising, and is found to be superior in most cases. A new, localized estimator of noise standard deviation is also obtained. Our work provides the first step in developing an adaptive denoising method for non-stationary noise.
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