UM
Joint medical image fusion, denoising and enhancement via discriminative low-rank sparse dictionaries learning
Li, Huafeng; He, Xiaoge; Tao, Dapeng; Tang, Yuanyan; Wang, Ruxin
2018-07
Source PublicationPATTERN RECOGNITION
ISSN0031-3203
Volume79Pages:130-146
AbstractMedical image fusion is important in image-guided medical diagnostics, treatment, and other computer vision tasks. However, most current approaches assume that the source images are noise-free, which is not usually the case in practice. The performance of traditional fusion methods decreases significantly when images are corrupted with noise. It is therefore necessary to develop a fusion method that accurately preserves detailed information even when images are corrupted. However, suppressing noise and enhancing textural details are difficult to achieve simultaneously. In this paper, we develop a novel medical image fusion, denoising, and enhancement method based on low-rank sparse component decomposition and dictionary learning. Specifically, to improve the discriminative ability of the learned dictionaries, we incorporate low-rank and sparse regularization terms into the dictionary learning model. Furthermore, in the image decomposition model, we impose a weighted nuclear norm and sparse constraint on the sparse component to remove noise and preserve textural details. Finally, the fused result is constructed by combining the fused low-rank and sparse components of the source images. Experimental results demonstrate that the proposed method consistently outperforms existing state-of-the-art methods in terms of both visual and quantitative evaluations. (C) 2018 Elsevier Ltd. All rights reserved.
KeywordMedical image fusion Denoising Dictionary learning Low-rank decomposition Sparse representation
DOI10.1016/j.patcog.2018.02.005
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000430903000010
PublisherELSEVIER SCI LTD
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:54   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Li, Huafeng,He, Xiaoge,Tao, Dapeng,et al. Joint medical image fusion, denoising and enhancement via discriminative low-rank sparse dictionaries learning[J]. PATTERN RECOGNITION,2018,79:130-146.
APA Li, Huafeng,He, Xiaoge,Tao, Dapeng,Tang, Yuanyan,&Wang, Ruxin.(2018).Joint medical image fusion, denoising and enhancement via discriminative low-rank sparse dictionaries learning.PATTERN RECOGNITION,79,130-146.
MLA Li, Huafeng,et al."Joint medical image fusion, denoising and enhancement via discriminative low-rank sparse dictionaries learning".PATTERN RECOGNITION 79(2018):130-146.
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