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Infrared Small-Target Detection Using Multidirectional Local Difference Measure Weighted by Entropy

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成果类型:
期刊论文
作者:
Yao, Huang;Liu, Liping;Wei, Yantao;Chen, Di;Tong, Mingwen
通讯作者:
Yantao Wei
作者机构:
[Yao, Huang; Wei, Yantao; Chen, Di; Liu, Liping; Tong, Mingwen] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.
通讯机构:
[Yantao Wei] A
Author to whom correspondence should be addressed.
语种:
英文
关键词:
small-target detection;infrared image;directional local difference measure;entropy
期刊:
Sustainability
ISSN:
2071-1050
年:
2023
卷:
15
期:
3
页码:
1902-
基金类别:
This work was supported in part by the National Natural Science Foundation of China under grant 62277029, and the Fundamental Research Funds for the Central Universities under grants CCNU22JC025, CCNU22JC011, CCNU20ZN002, CCNU20TD005.
机构署名:
本校为第一机构
摘要:
Detecting small targets from infrared remote sensing images is still a challenging task. In this research, we propose a multidirectional local difference measure weighted by entropy (MDLDE) to detect small targets from infrared images with messy backgrounds. First, a new multidirectional local difference measure is proposed to suppress the clutter background. Then, the entropy, which captures the overall heterogeneity between the target and the background, is utilized to enhance the target. Lastly, an adaptive threshold was adopted to segment the target region from the background. The designed...

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