TY - GEN
T1 - Iterated nonlocal means for texture restoration
AU - Brox, Thomas
AU - Cremers, Daniel
PY - 2007
Y1 - 2007
N2 - The recent nonlocal means filter is a very successful technique for denoising textured images. In this paper, we formulate a variational technique that leads to an adaptive version of this filter. In particular, in an iterative manner, the filtering result is employed to redefine the similarity of patches in the next iteration. We further introduce the idea to replace the neighborhood weighting by a sorting criterion. This addresses the parameter selection problem of the original nonlocal means filter and leads to favorable denoising results of textured images, particularly in case of large noise levels.
AB - The recent nonlocal means filter is a very successful technique for denoising textured images. In this paper, we formulate a variational technique that leads to an adaptive version of this filter. In particular, in an iterative manner, the filtering result is employed to redefine the similarity of patches in the next iteration. We further introduce the idea to replace the neighborhood weighting by a sorting criterion. This addresses the parameter selection problem of the original nonlocal means filter and leads to favorable denoising results of textured images, particularly in case of large noise levels.
UR - http://www.scopus.com/inward/record.url?scp=37249000010&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-72823-8_2
DO - 10.1007/978-3-540-72823-8_2
M3 - Conference contribution
AN - SCOPUS:37249000010
SN - 9783540728221
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 13
EP - 24
BT - Scale Space and Variational Methods in Computer Vision, First International Conference, SSVM 2007, Proceedings
PB - Springer Verlag
T2 - 1st International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2007
Y2 - 30 May 2007 through 2 June 2007
ER -