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 …
Deep learning for pixel-level image fusion: Recent advances and future prospects
By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …
composite image, pixel-level image fusion is recognized as having high significance in a …
SDNet: A versatile squeeze-and-decomposition network for real-time image fusion
In this paper, a squeeze-and-decomposition network (SDNet) is proposed to realize multi-
modal and digital photography image fusion in real time. Firstly, we generally transform …
modal and digital photography image fusion in real time. Firstly, we generally transform …
DDcGAN: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion
In this paper, we proposed a new end-to-end model, termed as dual-discriminator
conditional generative adversarial network (DDcGAN), for fusing infrared and visible images …
conditional generative adversarial network (DDcGAN), for fusing infrared and visible images …
Rethinking the image fusion: A fast unified image fusion network based on proportional maintenance of gradient and intensity
In this paper, we propose a fast unified image fusion network based on proportional
maintenance of gradient and intensity (PMGI), which can end-to-end realize a variety of …
maintenance of gradient and intensity (PMGI), which can end-to-end realize a variety of …
Infrared and visible image fusion methods and applications: A survey
Infrared images can distinguish targets from their backgrounds based on the radiation
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …
Deep learning-based multi-focus image fusion: A survey and a comparative study
X Zhang - IEEE Transactions on Pattern Analysis and Machine …, 2021 - ieeexplore.ieee.org
Multi-focus image fusion (MFIF) is an important area in image processing. Since 2017, deep
learning has been introduced to the field of MFIF and various methods have been proposed …
learning has been introduced to the field of MFIF and various methods have been proposed …
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 …
Image fusion with convolutional sparse representation
As a popular signal modeling technique, sparse representation (SR) has achieved great
success in image fusion over the last few years with a number of effective algorithms being …
success in image fusion over the last few years with a number of effective algorithms being …
A phase congruency and local Laplacian energy based multi-modality medical image fusion method in NSCT domain
Z Zhu, M Zheng, G Qi, D Wang, Y Xiang - IEEE Access, 2019 - ieeexplore.ieee.org
Multi-modality image fusion provides more comprehensive and sophisticated information in
modern medical diagnosis, remote sensing, video surveillance, and so on. This paper …
modern medical diagnosis, remote sensing, video surveillance, and so on. This paper …