Multi-focus Image Fusion Algorithm Based on Multilevel Morphological Component Analysis
- https://doi.org/10.2991/ifmca-16.2017.40How to use a DOI?
- multilevel morphological component analysis; multi-focus image fusion; feature vectors; weighted fusion rules.
This study proposed a novel image fusion algorithm based on weighed multilevel morphological component analysis (FWMMCA). First, morphological component analysis is improved into a new multi-scale decomposition algorithm–multilevel morphological component analysis (MMCA). Then, feature vectors are extracted from MMCA sub images, which are used to reflect brightness, texture regularity, energy, and randomness of those images. Moreover, the feature vectors are innovatively used as weight in fusion rules, to propose a weighted fusion rules. Sub images are fused via those fusion rules, which are finally reconstituted into fused image.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Lingling Wang AU - Xiongfei Li PY - 2017/03 DA - 2017/03 TI - Multi-focus Image Fusion Algorithm Based on Multilevel Morphological Component Analysis BT - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016) PB - Atlantis Press SP - 248 EP - 252 SN - 2352-5401 UR - https://doi.org/10.2991/ifmca-16.2017.40 DO - https://doi.org/10.2991/ifmca-16.2017.40 ID - Wang2017/03 ER -