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 …
MATR: Multimodal medical image fusion via multiscale adaptive transformer
Owing to the limitations of imaging sensors, it is challenging to obtain a medical image that
simultaneously contains functional metabolic information and structural tissue details …
simultaneously contains functional metabolic information and structural tissue details …
YDTR: Infrared and visible image fusion via Y-shape dynamic transformer
Infrared and visible image fusion is aims to generate a composite image that can
simultaneously describe the salient target in the infrared image and texture details in the …
simultaneously describe the salient target in the infrared image and texture details in the …
DATFuse: Infrared and visible image fusion via dual attention transformer
The fusion of infrared and visible images aims to generate a composite image that can
simultaneously contain the thermal radiation information of an infrared image and the …
simultaneously contain the thermal radiation information of an infrared image and the …
Degradation-resistant unfolding network for heterogeneous image fusion
Heterogeneous image fusion (HIF) techniques aim to enhance image quality by merging
complementary information from images captured by different sensors. Among these …
complementary information from images captured by different sensors. Among these …
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 …
Transmef: A transformer-based multi-exposure image fusion framework using self-supervised multi-task learning
In this paper, we propose TransMEF, a transformer-based multi-exposure image fusion
framework that uses self-supervised multi-task learning. The framework is based on an …
framework that uses self-supervised multi-task learning. The framework is based on an …
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 …
A general framework for image fusion based on multi-scale transform and sparse representation
In image fusion literature, multi-scale transform (MST) and sparse representation (SR) are
two most widely used signal/image representation theories. This paper presents a general …
two most widely used signal/image representation theories. This paper presents a general …