Multilateral Filtering: a Novel Framework for Generic Similarity-based Image Denoising
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.
- Published Version
Download (276Kb) | Preview
Official URL: http://doi.ieeecomputersociety.org/10.1109/ICIP.20...
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|
Actions (login required)