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ICIAP
2009
ACM

Nonlocal Similarity Image Filtering

14 years 4 months ago
Nonlocal Similarity Image Filtering
Abstract. We exploit the recurrence of structures at different locations, orientations and scales in an image to perform denoising. While previous methods based on "nonlocal filtering" identify corresponding patches only up to translations, we consider more general similarity transformations. Due to the additional computational burden, we break the problem down into two steps: First, we extract similarity invariant descriptors at each pixel location; second, we search for similar patches by matching descriptors. The descriptors used are inspired by scale-invariant feature transform (SIFT), whereas the similarity search is solved via the minimization of a cost function adapted from local denoising methods. Our method compares favorably with existing denoising algorithms as tested on several datasets.
Yifei Lou, Paolo Favaro, Stefano Soatto, Andrea L.
Added 24 Nov 2009
Updated 24 Nov 2009
Type Conference
Year 2009
Where ICIAP
Authors Yifei Lou, Paolo Favaro, Stefano Soatto, Andrea L. Bertozzi
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