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- Title
Patch-based and multiresolution optimum bilateral filters for denoising images corrupted by Gaussian noise.
- Authors
Kishan, Harini; Seelamantula, Chandra Sekhar
- Abstract
We propose optimal bilateral filtering techniques for Gaussian noise suppression in images. To achieve maximum denoising performance via optimal filter parameter selection, we adopt Stein's unbiased risk estimate (SURE)--an unbiased estimate of the mean-squared error (MSE). Unlike MSE, SURE is independent of the ground truth and can be used in practical scenarios where the ground truth is unavailable. In our recent work, we derived SURE expressions in the context of the bilateral filter and proposed SURE-optimal bilateral filter (SOBF). We selected the optimal parameters of SOBF using the SURE criterion. To further improve the denoising performance of SOBF, we propose variants of SOBF, namely, SURE-optimal multiresolution bilateral filter (SMBF), which involves optimal bilateral filtering in a wavelet framework, and SURE-optimal patchbased bilateral filter (SPBF), where the bilateral filter parameters are optimized on small image patches. Using SURE guarantees automated parameter selection. The multiresolution and localized denoising in SMBF and SPBF, respectively, yield superior denoising performance when compared with the globally optimal SOBF. Experimental validations and comparisons show that the proposed denoisers perform on par with some state-of-the-art denoising techniques.
- Subjects
SIGNAL denoising; RANDOM noise theory; DIGITAL image processing; WAVELET transforms; PIXELS
- Publication
Journal of Electronic Imaging, 2015, Vol 24, Issue 5, p053021-1
- ISSN
1017-9909
- Publication type
Article
- DOI
10.1117/1.JEI.24.5.053021