Abstract
We consider the role of scale in the context of the recently-developed non-local-means (NL-means) filter. A new example-based variant of the NL-means is introduced and results based on same-scale and cross-scale counterparts will be compared for a set of images. We consider the cases in which neighborhoods are taken from the observed image itself as well as from other irrelevant images, varying the smoothness parameter as well. Our experiments indicate that using cross-scale (i.e., downsampled) neighborhoods in the NL-means filter yields results that are quite comparable to those obtained by using neighborhoods at the same-scale.
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Ebrahimi, M., Vrscay, E.R. (2008). Examining the Role of Scale in the Context of the Non-Local-Means Filter. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_17
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DOI: https://doi.org/10.1007/978-3-540-69812-8_17
Publisher Name: Springer, Berlin, Heidelberg
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