Butt, I. and Rajpoot, Nasir M. (Nasir Mahmood) (2009) Multilateral filtering : a novel framework for generic similarity-based image denoising. In: 16th IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, 7-10 Nov, 2009. Published in: 16th IEEE International Conference on Image Processing (ICIP 2009) pp. 2981-2984.

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Abstract

We present a novel iterative nonlinear filtering framework, termed multilateral filtering, based on the idea of generic local similarity. A set of local features is computed for each pixel using its local neighborhood. Two pixels are considered to be similar if the Euclidean distance between their corresponding feature vectors is small and vice versa. Multilateral filtering results in image smoothing while preserving edge and textural features. Our experimental results show that the proposed method produces comparable and often better results than the state-of-the-art denoising methods.

Item Type:	Conference Item (Paper)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science > Computer Science
Journal or Publication Title:	16th IEEE International Conference on Image Processing (ICIP 2009)
Publisher:	IEEE
ISSN:	1522-4880
Date:	2009
Page Range:	pp. 2981-2984
Identification Number:	10.1109/ICIP.2009.5414513
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Conference Paper Type:	Paper
Title of Event:	16th IEEE International Conference on Image Processing (ICIP 2009)
Type of Event:	Conference
Location of Event:	Cairo, Egypt
Date(s) of Event:	7-10 Nov, 2009
Related URLs:	Other Repository
URI:	http://wrap.warwick.ac.uk/id/eprint/47499

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