Low-Light Image Enhancement Based on Wavelet Local and Global Feature Fusion Network Article Swipe
Shun Song
,
Xiangqian Jiang
,
Dawei Zhao
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26689/jcer.v9i11.12894
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26689/jcer.v9i11.12894
A wavelet-based local and global feature fusion network (LAGN) is proposed for low-light image enhancement, aiming to enhance image details and restore colors in dark areas. This study focuses on addressing three key issues in low-light image enhancement: Enhancing low-light images using LAGN to preserve image details and colors; extracting image edge information via wavelet transform to enhance image details; and extracting local and global features of images through convolutional neural networks and Transformer to improve image contrast. Comparisons with state-of-the-art methods on two datasets verify that LAGN achieves the best performance in terms of details, brightness, and contrast.
Related Topics
Concepts
Artificial intelligence
Image fusion
Pattern recognition (psychology)
Computer science
Computer vision
Image (mathematics)
Wavelet transform
Feature (linguistics)
Convolutional neural network
Feature detection (computer vision)
Image gradient
Wavelet
Image restoration
Feature extraction
Image segmentation
Image texture
Image enhancement
Top-hat transform
Image processing
Key (lock)
Fusion
Artificial neural network
Enhanced Data Rates for GSM Evolution
Composite image filter
Metadata
- Type
- article
- Landing Page
- https://doi.org/10.26689/jcer.v9i11.12894
- https://ojs.bbwpublisher.com/index.php/JCER/article/download/12894/11202
- OA Status
- diamond
- OpenAlex ID
- https://openalex.org/W7109949705
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7109949705Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.26689/jcer.v9i11.12894Digital Object Identifier
- Title
-
Low-Light Image Enhancement Based on Wavelet Local and Global Feature Fusion NetworkWork title
- Type
-
articleOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-08Full publication date if available
- Authors
-
Shun Song, Xiangqian Jiang, Dawei ZhaoList of authors in order
- Landing page
-
https://doi.org/10.26689/jcer.v9i11.12894Publisher landing page
- PDF URL
-
https://ojs.bbwpublisher.com/index.php/JCER/article/download/12894/11202Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://ojs.bbwpublisher.com/index.php/JCER/article/download/12894/11202Direct OA link when available
- Concepts
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Artificial intelligence, Image fusion, Pattern recognition (psychology), Computer science, Computer vision, Image (mathematics), Wavelet transform, Feature (linguistics), Convolutional neural network, Feature detection (computer vision), Image gradient, Wavelet, Image restoration, Feature extraction, Image segmentation, Image texture, Image enhancement, Top-hat transform, Image processing, Key (lock), Fusion, Artificial neural network, Enhanced Data Rates for GSM Evolution, Composite image filterTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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