Multi-focus image fusion: A survey of the state of the art
Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …
lenses by creating an all-in-focus image from a set of partially focused images of the same …
Multi-focus image fusion with a deep convolutional neural network
As is well known, activity level measurement and fusion rule are two crucial factors in image
fusion. For most existing fusion methods, either in spatial domain or in a transform domain …
fusion. For most existing fusion methods, either in spatial domain or in a transform domain …
Review of various image fusion algorithms and image fusion performance metric
Image fusion is the process in which substantial information taken through different sensors,
different exposure values and at different focus points is integrated together to generate a …
different exposure values and at different focus points is integrated together to generate a …
Image segmentation-based multi-focus image fusion through multi-scale convolutional neural network
C Du, S Gao - IEEE access, 2017 - ieeexplore.ieee.org
A decision map contains complete and clear information about the image to be fused, and
detecting the decision map is crucial to various image fusion issues, especially multi-focus …
detecting the decision map is crucial to various image fusion issues, especially multi-focus …
Multi-focus image fusion with a natural enhancement via a joint multi-level deeply supervised convolutional neural network
Common non-focused areas are often present in multi-focus images due to the limitation of
the number of focused images. This factor severely degrades the fusion quality of multi-focus …
the number of focused images. This factor severely degrades the fusion quality of multi-focus …
Multi-focus image fusion based on nonsubsampled contourlet transform and residual removal
X Li, F Zhou, H Tan, Y Chen, W Zuo - Signal Processing, 2021 - Elsevier
The goal of multi-focus image fusion is to integrate all focus pixels from the source images
into the fused result and simultaneously avoid the introduction of defocused pixels …
into the fused result and simultaneously avoid the introduction of defocused pixels …
A novel dictionary learning approach for multi-modality medical image fusion
Z Zhu, Y Chai, H Yin, Y Li, Z Liu - Neurocomputing, 2016 - Elsevier
Multi-modality medical image fusion technology can integrate the complementary
information of different modality medical images, obtain more precise, reliable and better …
information of different modality medical images, obtain more precise, reliable and better …
Infrared and visible image fusion scheme based on NSCT and low-level visual features
Multi-scale transform (MST) is an efficient tool for image fusion. Recently, many fusion
methods have been developed based on different MSTs, and they have shown potential …
methods have been developed based on different MSTs, and they have shown potential …
Discriminative dictionary learning-based multiple component decomposition for detail-preserving noisy image fusion
How to effectively preserve the fine-scale details of the image when noises are suppressed
is one of the great challenges faced by scholars in the field of noisy image fusion. The …
is one of the great challenges faced by scholars in the field of noisy image fusion. The …
An image fusion method based on sparse representation and sum modified-Laplacian in NSCT domain
Y Li, Y Sun, X Huang, G Qi, M Zheng, Z Zhu - Entropy, 2018 - mdpi.com
Multi-modality image fusion provides more comprehensive and sophisticated information in
modern medical diagnosis, remote sensing, video surveillance, etc. Traditional multi-scale …
modern medical diagnosis, remote sensing, video surveillance, etc. Traditional multi-scale …