Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23563
Title: A novel adaptive SVR based filter ASBF for image restoration
Authors: Zhu, J
Wang, S
Wu, X
Chung, FL 
Keywords: Adaptive filter
Image restoration
Median filter
Support vector regression
Issue Date: 2006
Publisher: Springer
Source: Soft computing, 2006, v. 10, no. 8, p. 665-672 How to cite?
Journal: Soft computing 
Abstract: In this paper, a novel adaptive filter ASBF based on support vector regression (SVR) is proposed to preserve more image details and efficiently suppress impulse noise simultaneously. The main idea of the novel filter ASBF here is to employ a SVR based impulse detector to judge whether an input pixel is contaminated or not by impulse noise. If this case happens, a median filter is employed to remove the corresponding impulse noise. This judg ment procedure is executed by regressing the filter window of an input pixel using SVR and then judging the input pixel by its regression distance. Huber loss function is used in SVR regression, due to its excellent robustness capability. The distinctive advantage of the filter ASBF over the latest Support Vector Classifier (SVC) based filter is that no training for the original noise-free image is required in our approach, which is well in accordance with our visual judgment way. Experimental results for benchmark images demonstrate that our filter ASBF here outperforms the extensively-used median-based filters and the SVC based filter.
URI: http://hdl.handle.net/10397/23563
ISSN: 1432-7643
DOI: 10.1007/s00500-005-0536-2
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

3
Last Week
0
Last month
0
Citations as of Nov 10, 2017

WEB OF SCIENCETM
Citations

2
Last Week
0
Last month
0
Citations as of Nov 16, 2017

Page view(s)

43
Last Week
1
Last month
Checked on Nov 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.