Multiresolution Bilateral Filtering for Image Denoising
By Ming Zhang, Bahadir K. Gunturk. IEEE Transactions on Image Processing, 2008
517 citations recorded by the source corpus.
The bilateral filter is a nonlinear filter that does spatial averaging without smoothing edges; it has shown to be an effective image denoising technique. An important issue with the application of the bilateral filter is the selection of the filter parameters, which affect the results significantly. There are two main contributions of this paper. The first contribution is an empirical study of the optimal bilateral filter parameter selection in image denoising applications. The second contribution is an extension of the bilateral filter: multiresolution bilateral filter, where bilateral filtering is applied to the approximation (low-frequency) subbands of a signal decomposed using a wavelet filter bank. The multiresolution bilateral filter is combined with wavelet thresholding to form a new image denoising framework, which turns out to be very effective in eliminating noise in real noisy images. Experimental results with both simulated and real data are provided.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/44344182306f0fa504e472c139ff38109249107f
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In Computer Vision and Pattern Recognition
In Media Technology
Citations in the corpus
- Image fusion based on pixel significance using cross bilateral filter (2013, methodology): “Since σ s and σ r control the behavior of BF, the dependency of σ r /σ s values and derivative of the input signal on the behaviors of the BF are analyzed in Zhang and Gunturk [28].”