CLC number: TP701
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2011-05-05
Cited: 5
Clicked: 9136
Wen-de Dong, Yue-ting Chen, Zhi-hai Xu, Hua-jun Feng, Qi Li. Image stabilization with support vector machine[J]. Journal of Zhejiang University Science C, 2011, 12(6): 478-485.
@article{title="Image stabilization with support vector machine",
author="Wen-de Dong, Yue-ting Chen, Zhi-hai Xu, Hua-jun Feng, Qi Li",
journal="Journal of Zhejiang University Science C",
volume="12",
number="6",
pages="478-485",
year="2011",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1000236"
}
%0 Journal Article
%T Image stabilization with support vector machine
%A Wen-de Dong
%A Yue-ting Chen
%A Zhi-hai Xu
%A Hua-jun Feng
%A Qi Li
%J Journal of Zhejiang University SCIENCE C
%V 12
%N 6
%P 478-485
%@ 1869-1951
%D 2011
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1000236
TY - JOUR
T1 - Image stabilization with support vector machine
A1 - Wen-de Dong
A1 - Yue-ting Chen
A1 - Zhi-hai Xu
A1 - Hua-jun Feng
A1 - Qi Li
J0 - Journal of Zhejiang University Science C
VL - 12
IS - 6
SP - 478
EP - 485
%@ 1869-1951
Y1 - 2011
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1000236
Abstract: We propose an image stabilization method based on support vector machine (SVM). Since SVM is very effective in solving nonlinear regression problems, an SVM model was constructed and trained to simulate the vibration characteristic. Then this model was used to predict and compensate for the vibration. A simulation system was built and four assessment metrics including the signal-to-noise ratio (SNR), gray mean gradient (GMG), Laplacian (LAP), and modulation transfer function (MTF) were used to verify our approach. Experimental results showed that this new method allows the image plane to locate stably on the CCD, and high quality images can be obtained.
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