Nonlocal Similarity Image Filtering

Authors:
Yifei Lou;Paolo Favaro;Stefano Soatto;Andrea Bertozzi
Affiliations:
University of California Los Angeles, USA;Joint Research Institute on Image and Signal processing, Heriot-Watt University, Edinburgh, UK;University of California Los Angeles, USA;University of California Los Angeles, USA
Venue:
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Year:
2009

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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.