Variational image fusion approach based on TGV and local information
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 g...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-06-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2017.0451 |
| Summary: | 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. |
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| ISSN: | 1751-9632 1751-9640 |