Image Restoration by Spatial Clustering
Summary :
A method based on clustering is presented for restoring and segmenting gray scale images. An optimum clustering obtained by a gradient method gives an image with gray scale values which vary smoothly in each segmented region. The method is also applied to restoration from sparsely sampled data.
- Publication
- IEICE TRANSACTIONS on Information Vol.E79-D No.7 pp.1000-1003
- Publication Date
- 1996/07/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Image Processing,Computer Graphics and Pattern Recognition
Authors
Keyword
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Hiroto SHINGAI, Hiroyuki MATSUNAGA, Kiichi URAHAMA, "Image Restoration by Spatial Clustering" in IEICE TRANSACTIONS on Information,
vol. E79-D, no. 7, pp. 1000-1003, July 1996, doi: .
Abstract: A method based on clustering is presented for restoring and segmenting gray scale images. An optimum clustering obtained by a gradient method gives an image with gray scale values which vary smoothly in each segmented region. The method is also applied to restoration from sparsely sampled data.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_7_1000/_p
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@ARTICLE{e79-d_7_1000,
author={Hiroto SHINGAI, Hiroyuki MATSUNAGA, Kiichi URAHAMA, },
journal={IEICE TRANSACTIONS on Information},
title={Image Restoration by Spatial Clustering},
year={1996},
volume={E79-D},
number={7},
pages={1000-1003},
abstract={A method based on clustering is presented for restoring and segmenting gray scale images. An optimum clustering obtained by a gradient method gives an image with gray scale values which vary smoothly in each segmented region. The method is also applied to restoration from sparsely sampled data.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - Image Restoration by Spatial Clustering
T2 - IEICE TRANSACTIONS on Information
SP - 1000
EP - 1003
AU - Hiroto SHINGAI
AU - Hiroyuki MATSUNAGA
AU - Kiichi URAHAMA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 1996
AB - A method based on clustering is presented for restoring and segmenting gray scale images. An optimum clustering obtained by a gradient method gives an image with gray scale values which vary smoothly in each segmented region. The method is also applied to restoration from sparsely sampled data.
ER -
English
