IEICE TRANSACTIONS on Information
A Novel Search Approach for Blur Kernel Estimation of Defocused Image Restoration
Summary :
In this letter, we propose a novel search approach to blur kernel estimation for defocused image restoration. An adaptive binary search on consensus is the main contribution of our research. It is based on binary search and random sample consensus set (RANSAC). Moreover an evaluating function which uses a histogram of gradient distribution is proposed for assessing restored images. Simulations on an image benchmark dataset shows that the proposed algorithm can estimate, on average, the blur kernels 15.14% more accurately than other defocused image restoration algorithms.
- Publication
- IEICE TRANSACTIONS on Information Vol.E96-D No.3 pp.754-757
- Publication Date
- 2013/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E96.D.754
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Keyword
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Sangwoo AHN, Jongwha CHONG, "A Novel Search Approach for Blur Kernel Estimation of Defocused Image Restoration" in IEICE TRANSACTIONS on Information,
vol. E96-D, no. 3, pp. 754-757, March 2013, doi: 10.1587/transinf.E96.D.754.
Abstract: In this letter, we propose a novel search approach to blur kernel estimation for defocused image restoration. An adaptive binary search on consensus is the main contribution of our research. It is based on binary search and random sample consensus set (RANSAC). Moreover an evaluating function which uses a histogram of gradient distribution is proposed for assessing restored images. Simulations on an image benchmark dataset shows that the proposed algorithm can estimate, on average, the blur kernels 15.14% more accurately than other defocused image restoration algorithms.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E96.D.754/_p
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@ARTICLE{e96-d_3_754,
author={Sangwoo AHN, Jongwha CHONG, },
journal={IEICE TRANSACTIONS on Information},
title={A Novel Search Approach for Blur Kernel Estimation of Defocused Image Restoration},
year={2013},
volume={E96-D},
number={3},
pages={754-757},
abstract={In this letter, we propose a novel search approach to blur kernel estimation for defocused image restoration. An adaptive binary search on consensus is the main contribution of our research. It is based on binary search and random sample consensus set (RANSAC). Moreover an evaluating function which uses a histogram of gradient distribution is proposed for assessing restored images. Simulations on an image benchmark dataset shows that the proposed algorithm can estimate, on average, the blur kernels 15.14% more accurately than other defocused image restoration algorithms.},
keywords={},
doi={10.1587/transinf.E96.D.754},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - A Novel Search Approach for Blur Kernel Estimation of Defocused Image Restoration
T2 - IEICE TRANSACTIONS on Information
SP - 754
EP - 757
AU - Sangwoo AHN
AU - Jongwha CHONG
PY - 2013
DO - 10.1587/transinf.E96.D.754
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2013
AB - In this letter, we propose a novel search approach to blur kernel estimation for defocused image restoration. An adaptive binary search on consensus is the main contribution of our research. It is based on binary search and random sample consensus set (RANSAC). Moreover an evaluating function which uses a histogram of gradient distribution is proposed for assessing restored images. Simulations on an image benchmark dataset shows that the proposed algorithm can estimate, on average, the blur kernels 15.14% more accurately than other defocused image restoration algorithms.
ER -
English
