By Topic

Adaptive Rank Order Filter for Image Noise Removal

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Cheng-Hsiung Hsieh ; Dept. of Comput. Sci. & Inf. Eng., Chaoyang Univ. of Technol., Wufeng, Taiwan ; Po-Chin Huang

This paper presents an adaptive rank order filter (AROF) which is applied to image noise removal. By two observations on the adaptive median filter (AMF) in, the AROF is motivated and developed. First, the expansion of window size in the AMF is determine by the criterion if the median is a noisy pixel or not. This criterion is not appropriate when the noise density is moderate or high. Second, the pixels processed by the AMF are reused in the filtering of AMF. This doing degrades the visual quality of restored image. To avoid the two problems found in the AMF, we proposes the AROF. In the AROF, the criterion to expand window size is all pixels in the window are noisy. If it is not the case, the center pixel is replaced by either median or non-median whcih is not noisy. Moreover, the pixels processed by the AROF are not put into account in the following filtereing process. Simulation results show that the proposed AROF has better performance than the AMF when the noise density is moderate or high while remains similar PSNR to those for the AMF in the case of low noise density.

Published in:

Computer Science and Information Engineering, 2009 WRI World Congress on  (Volume:7 )

Date of Conference:

March 31 2009-April 2 2009