Variational image fusion approach based on TGV and local information
- Author(s): Qinxia Wang 1 and Xiaoping Yang 2
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View affiliations
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Affiliations:
1:
School of Science , Nanjing University of Science & Technology , Nanjing 210094 , Jiangsu , People's Republic of China ;
2: Department of Mathematics , Nanjing University , Nanjing 210093 , Jiangsu , People's Republic of China
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Affiliations:
1:
School of Science , Nanjing University of Science & Technology , Nanjing 210094 , Jiangsu , People's Republic of China ;
- Source:
Volume 12, Issue 4,
June
2018,
p.
535 – 541
DOI: 10.1049/iet-cvi.2017.0451 , Print ISSN 1751-9632, Online ISSN 1751-9640
In this study, the authors propose a variational approach based on total generalised variation (TGV) and local gradient information to fuse multi-focus images as well as medical images of computed tomography and magnetic resonance. They use the second-order TGV as the regularisation term and local gradient information as the fusion weight to extract image features. To compute the new model effectively, the primal-dual algorithm is carried out. Various experiments are made to verify the effectiveness of the proposed methods.
Inspec keywords: feature extraction; medical image processing; computerised tomography; gradient methods; biomedical MRI; image fusion
Other keywords: primal-dual algorithm; second-order TGV; local gradient information; image feature extraction; computed tomography; magnetic resonance; total generalised variation; medical images; variational image fusion approach
Subjects: Computer vision and image processing techniques; Interpolation and function approximation (numerical analysis); Interpolation and function approximation (numerical analysis); Image recognition; X-rays and particle beams (medical uses); Numerical approximation and analysis; Medical magnetic resonance imaging and spectroscopy; Patient diagnostic methods and instrumentation; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Biology and medical computing; Biomedical magnetic resonance imaging and spectroscopy
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