中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion

文献类型:期刊论文

作者E. Q. Zhang, L. H. Guo, J. D. Guo, S. F. Yan, X. Y. Li and L. S. Kong
刊名Applied Sciences-Basel
出版日期2023
卷号13期号:18页码:17
DOI10.3390/app131810230
英文摘要Images captured in low-brightness environments typically have low brightness, low contrast, and high noise levels, which significantly affect the overall image quality. To improve the image quality, a low-brightness image enhancement algorithm based on multi-scale fusion is proposed. First, a novel brightness transformation function is used for the generation of two images with different brightnesses. Then, the illumination estimation technique is used to construct a weight matrix, which facilitates the extraction of advantageous features from each image. Finally, the enhanced image is obtained by the fusion of two images using the weight matrix and the pyramid reconstruction algorithm. The proposed method has a better enhancement effect as shown by the experimental results. Compared to other image enhancement algorithms, it has lower evaluation values in the natural image quality evaluator (NIQE) and lightness order error (LOE) indices. The lowest average NIQE value of the proposed algorithm in each dataset is 2.836. This further demonstrates its superior performance.
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语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/68154]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714
E. Q. Zhang, L. H. Guo, J. D. Guo, S. F. Yan, X. Y. Li and L. S. Kong. A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion[J]. Applied Sciences-Basel,2023,13(18):17.
APA E. Q. Zhang, L. H. Guo, J. D. Guo, S. F. Yan, X. Y. Li and L. S. Kong.(2023).A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion.Applied Sciences-Basel,13(18),17.
MLA E. Q. Zhang, L. H. Guo, J. D. Guo, S. F. Yan, X. Y. Li and L. S. Kong."A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion".Applied Sciences-Basel 13.18(2023):17.

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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