Denoising Scheme for Realistic Digital Photos from Unknown Sources
Lim, Suk Hwan; Maurer, Ron; Kisilev, Pavel
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Abstract: This paper targets denoising of digital photos taken by cameras with unknown sensor parameters and image processing pipeline. Common noise characteristics in such images originate from camera-internal processing, such as demosaicing, tone mapping, and JPEG compression. Three of the noise characteristics that are not adequately addressed by existing denoising algorithms are spatially correlated low-frequency noise, strong signal dependency of the noise level and high levels of the chrominance noise relative to the luminance noise. We propose a generic scheme that extends existing denoisers such as the bilateral filter to account for all the problems above. Our solution combines a novel progressive pyramidal filtering scheme to address the correlated noise, filter adaptation via local noise level estimation and luminance-guided chrominance filtering to address the low-SNR of the chrominance channels. We demonstrate the effectiveness of our solution for challenging realistic noisy photos.
Additional Publication Information: Submitted to International Conference on Acoustic, Speech and Signal Processing 2009
External Posting Date: October 21, 2008 [Fulltext]. Approved for External Publication
Internal Posting Date: October 21, 2008 [Fulltext]