Joint medical image fusion, denoising and enhancement via discriminative low-rank sparse dictionaries learning
Medical image fusion is important in image-guided medical diagnostics, treatment, and other
computer vision tasks. However, most current approaches assume that the source images …
computer vision tasks. However, most current approaches assume that the source images …
Joint image fusion and denoising via three-layer decomposition and sparse representation
X Li, F Zhou, H Tan - Knowledge-Based Systems, 2021 - Elsevier
Image fusion has been received much attentions in recent years. However, solving both
noise-free image fusion and noise-perturbed image fusion problems remains a big …
noise-free image fusion and noise-perturbed image fusion problems remains a big …
Multi-modality medical image fusion based on separable dictionary learning and Gabor filtering
Q Hu, S Hu, F Zhang - Signal Processing: Image Communication, 2020 - Elsevier
Sparse representation (SR) has been widely used in image fusion in recent years. However,
source image, segmented into vectors, reduces correlation and structural information of …
source image, segmented into vectors, reduces correlation and structural information of …
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 …
Noise-robust image fusion with low-rank sparse decomposition guided by external patch prior
It is challenging to simultaneously achieve noise suppression and fine detail preservation in
noisy image fusion. To address this challenge, we propose a novel strategy for noisy image …
noisy image fusion. To address this challenge, we propose a novel strategy for noisy image …
Group-sparse representation with dictionary learning for medical image denoising and fusion
Recently, sparse representation has attracted a lot of interest in various areas. However, the
standard sparse representation does not consider the intrinsic structure, ie, the nonzero …
standard sparse representation does not consider the intrinsic structure, ie, the nonzero …
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 …
Simultaneous image fusion and denoising with adaptive sparse representation
In this study, a novel adaptive sparse representation (ASR) model is presented for
simultaneous image fusion and denoising. As a powerful signal modelling technique, sparse …
simultaneous image fusion and denoising. As a powerful signal modelling technique, sparse …
Medical image fusion based on sparse representation of classified image patches
J Zong, T Qiu - Biomedical Signal Processing and Control, 2017 - Elsevier
Medical image fusion is one of the hot research in the field of medical imaging and radiation
medicine, and is widely recognized by medical and engineering fields. In this paper, a new …
medicine, and is widely recognized by medical and engineering fields. In this paper, a new …
An improved approach for medical image fusion using sparse representation and Siamese convolutional neural network
Multimodal image fusion is a contemporary branch of medical imaging that aims to increase
the accuracy of clinical diagnosis of the disease stage development. The fusion of different …
the accuracy of clinical diagnosis of the disease stage development. The fusion of different …