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Journal of Electronic Imaging

Patch-based and multiresolution optimum bilateral filters for denoising images corrupted by Gaussian noise
Author(s): Harini Kishan; Chandra Sekhar Seelamantula
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Paper 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 patch-based 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.

Paper Details

Date Published: 6 October 2015
PDF: 15 pages
J. Electron. Imaging. 24(5) 053021 doi: 10.1117/1.JEI.24.5.053021
Published in: Journal of Electronic Imaging Volume 24, Issue 5
Show Author Affiliations
Harini Kishan, Indian Institute of Science (India)
Chandra Sekhar Seelamantula, Indian Institute of Science (India)


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