Butt, I. and Rajpoot, N.M. (2009) Multilateral Filtering: a Novel Framework for Generic Similarity-based Image Denoising. In: 16th IEEE International Conference on Image Processing (ICIP 2009), 7-10 November, 2009, Cairo, Egypt.

Preview

PDF - Published Version Download (276Kb) | Preview

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 or Workshop Item (Paper)
Uncontrolled Keywords:	combi denoising
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Science > Computer Science
Depositing User:	Jason Nurse
Date Deposited:	18 Dec 2010 12:28
Last Modified:	21 Mar 2012 11:00
URI:	http://eprints.dcs.warwick.ac.uk/id/eprint/450

Actions (login required)

View Item