The bilateral filter is a nonlinear filter that does spatial averaging without smoothing edges; it has shown to be an effective image denoising technique in addition to some other applications. There are two main contributions of this paper. First, we provide an empirical study of the optimal parameter selection for the bilateral filter in image denoising applications. Second, we present an extension of the bilateral filter: multi-resolution bilateral filter, where bilateral filtering is applied to low-frequency subbands of a signal decomposed using an orthogonal wavelet transform. Combined with wavelet thresholding, this new image denoising framework turns out to be very effective in eliminating noise in real noisy images. We provide experimental results with both simulated data and real data.
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