Abstract
We know one characteristic of image is that each pixel is very close to surrounding neighbors. If the impulsive noise appears in the local area, it will be very abruptly. In the proposed scheme, we pick up several neighboring pixels around the center pixel in the scanning window as the statistic factors. The mean value and mean of absolute neighboring difference (MAND) are utilized from those. Further, we use them to acquire a critical value. The value is a representative characteristic of those pixels in the local area and it will be used to identify whether if a pixel is corrupted.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 24th International Conference on Distributed Computing Systems Workshops |
| Editors | N.-F. Tzeng, M. Takizawa |
| Pages | 190-194 |
| Number of pages | 5 |
| Volume | 24 |
| Publication status | Published - 2004 Jul 12 |
| Event | Proceedings - 24th International Conference on Distributed Computing Systems Workshops - Hachioji, Japan Duration: 2004 Mar 23 → 2004 Mar 24 |
Other
| Other | Proceedings - 24th International Conference on Distributed Computing Systems Workshops |
|---|---|
| Country | Japan |
| City | Hachioji |
| Period | 04-03-23 → 04-03-24 |
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All Science Journal Classification (ASJC) codes
- Software
- Hardware and Architecture
- Computer Networks and Communications
Cite this
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High probability impulsive noise removal for corrupted images. / Hsiao, Ju Yuan; Chen, Shu Yi.
Proceedings - 24th International Conference on Distributed Computing Systems Workshops. ed. / N.-F. Tzeng; M. Takizawa. Vol. 24 2004. p. 190-194.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - High probability impulsive noise removal for corrupted images
AU - Hsiao, Ju Yuan
AU - Chen, Shu Yi
PY - 2004/7/12
Y1 - 2004/7/12
N2 - We know one characteristic of image is that each pixel is very close to surrounding neighbors. If the impulsive noise appears in the local area, it will be very abruptly. In the proposed scheme, we pick up several neighboring pixels around the center pixel in the scanning window as the statistic factors. The mean value and mean of absolute neighboring difference (MAND) are utilized from those. Further, we use them to acquire a critical value. The value is a representative characteristic of those pixels in the local area and it will be used to identify whether if a pixel is corrupted.
AB - We know one characteristic of image is that each pixel is very close to surrounding neighbors. If the impulsive noise appears in the local area, it will be very abruptly. In the proposed scheme, we pick up several neighboring pixels around the center pixel in the scanning window as the statistic factors. The mean value and mean of absolute neighboring difference (MAND) are utilized from those. Further, we use them to acquire a critical value. The value is a representative characteristic of those pixels in the local area and it will be used to identify whether if a pixel is corrupted.
UR - http://www.scopus.com/inward/record.url?scp=3042590263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=3042590263&partnerID=8YFLogxK
M3 - Conference contribution
VL - 24
SP - 190
EP - 194
BT - Proceedings - 24th International Conference on Distributed Computing Systems Workshops
A2 - Tzeng, N.-F.
A2 - Takizawa, M.
ER -