A novel multi-modality image fusion method based on image decomposition and sparse representation
Z Zhu, H Yin, Y Chai, Y Li, G Qi - Information Sciences, 2018 - Elsevier
Multi-modality image fusion is an effective technique to fuse the complementary information
from multi-modality images into an integrated image. The additional information can not only …
from multi-modality images into an integrated image. The additional information can not only …
[HTML][HTML] Multimodal image fusion via coupled feature learning
This paper presents a multimodal image fusion method using a novel decomposition model
based on coupled dictionary learning. The proposed method is general and can be used for …
based on coupled dictionary learning. The proposed method is general and can be used for …
Multimodal image fusion with joint sparsity model
H Yin, S Li - Optical Engineering, 2011 - spiedigitallibrary.org
Image fusion combines multiple images of the same scene into a single image which is
suitable for human perception and practical applications. Different images of the same …
suitable for human perception and practical applications. Different images of the same …
Visual attention guided image fusion with sparse representation
B Yang, S Li - Optik, 2014 - Elsevier
Image fusion techniques aim at transferring useful information from the input source images
to the fused image. The common assumption for most fusion approaches is that the useful …
to the fused image. The common assumption for most fusion approaches is that the useful …
A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application
The objective of image fusion is to combine information from multiple images of the same
scene. The result of image fusion is a single image which is more suitable for human and …
scene. The result of image fusion is a single image which is more suitable for human and …
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 …
Multi-modal medical image fusion based on two-scale image decomposition and sparse representation
S Maqsood, U Javed - Biomedical Signal Processing and Control, 2020 - Elsevier
Multimodality image fusion is the hot topic in medical imaging field which increases the
clinical diagnosis accuracy through fusing complementary information of multimodality …
clinical diagnosis accuracy through fusing complementary information of multimodality …
Fast filtering image fusion
K Zhan, Y Xie, H Wang, Y Min - Journal of Electronic Imaging, 2017 - spiedigitallibrary.org
Image fusion aims at exploiting complementary information in multimodal images to create a
single composite image with extended information content. An image fusion framework is …
single composite image with extended information content. An image fusion framework is …
Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review
As a result of several successful applications in computer vision and image processing,
sparse representation (SR) has attracted significant attention in multi-sensor image fusion …
sparse representation (SR) has attracted significant attention in multi-sensor image fusion …
Pixel-level image fusion with simultaneous orthogonal matching pursuit
B Yang, S Li - Information fusion, 2012 - Elsevier
Pixel-level image fusion integrates the information from multiple images of one scene to get
an informative image which is more suitable for human visual perception or further image …
an informative image which is more suitable for human visual perception or further image …