An Adaptive Focal Connectivity Algorithm for Multifocus Fusion
Abstract
Multifocus fusion is the process of fusing focal information from a set of input images into one all-in-focus image. Here, a versatile multifocus fusion algorithm is presented for application-independent fusion. A focally connected region is a region or a set of regions in an input image that falls under the depth of field of the imaging system. Such regions are segmented adaptively under the predicate of focal connectivity and fused by partition synthesis. The fused image has information from all focal planes, while maintaining the visual verisimilitude of the scene. In order to validate the fusion performance of our method, we have compared our results with those of tiling and multiscale fusion techniques. In addition to performing a seamless fusion of the focally connected regions, our method out performs the competing methods regarding overall sharpness in all our experiments. Several illustrative examples of multifocus fusion are shown and objective comparisons are provided.
Cite
Text
Hariharan et al. "An Adaptive Focal Connectivity Algorithm for Multifocus Fusion." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383434Markdown
[Hariharan et al. "An Adaptive Focal Connectivity Algorithm for Multifocus Fusion." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/hariharan2007cvpr-adaptive/) doi:10.1109/CVPR.2007.383434BibTeX
@inproceedings{hariharan2007cvpr-adaptive,
title = {{An Adaptive Focal Connectivity Algorithm for Multifocus Fusion}},
author = {Hariharan, Harishwaran and Koschan, Andreas F. and Abidi, Mongi A.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2007},
doi = {10.1109/CVPR.2007.383434},
url = {https://mlanthology.org/cvpr/2007/hariharan2007cvpr-adaptive/}
}