An Image Fusion Method Based on Sparse Representation and Sum Modified-Laplacian in NSCT Domain Article Swipe
Yuanyuan Li
,
Yanjing Sun
,
Xinhua Huang
,
Guanqiu Qi
,
Mingyao Zheng
,
Zhiqin Zhu
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.3390/e20070522
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.3390/e20070522
Multi-modality image fusion provides more comprehensive and sophisticated information in modern medical diagnosis, remote sensing, video surveillance, etc. Traditional multi-scale transform (MST) based image fusion solutions have difficulties in the selection of decomposition level, and the contrast loss in fused image. At the same time, traditional sparse-representation based image fusion methods suffer the weak representation ability of fixed dictionary. In order to overcome these deficiencies of MST- and SR-based methods, this paper proposes an image fusion framework which integrates nonsubsampled contour transformation (NSCT) into sparse representation (SR). In this fusion framework, NSCT is applied to source images decomposition for obtaining corresponding low- and high-pass coefficients. It fuses low- and high-pass coefficients by using SR and Sum Modified-laplacian (SML) respectively. NSCT inversely transforms the fused coefficients to obtain the final fused image. In this framework, a principal component analysis (PCA) is implemented in dictionary training to reduce the dimension of learned dictionary and computation costs. A novel high-pass fusion rule based on SML is applied to suppress pseudo-Gibbs phenomena around singularities of fused image. Compared to three mainstream image fusion solutions, the proposed solution achieves better performance on structural similarity and detail preservation in fused images.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/e20070522
- OA Status
- gold
- Cited By
- 84
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2828601215
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2828601215Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/e20070522Digital Object Identifier
- Title
-
An Image Fusion Method Based on Sparse Representation and Sum Modified-Laplacian in NSCT DomainWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-07-11Full publication date if available
- Authors
-
Yuanyuan Li, Yanjing Sun, Xinhua Huang, Guanqiu Qi, Mingyao Zheng, Zhiqin ZhuList of authors in order
- Landing page
-
https://doi.org/10.3390/e20070522Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3390/e20070522Direct OA link when available
- Concepts
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Contourlet, Image fusion, Sparse approximation, Artificial intelligence, Pattern recognition (psychology), Computer science, Image (mathematics), Fusion rules, Principal component analysis, Transformation (genetics), Mathematics, Wavelet transform, Wavelet, Gene, Chemistry, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
84Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 11, 2024: 6, 2023: 7, 2022: 15, 2021: 22Per-year citation counts (last 5 years)
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52Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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