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Visible and NIR Image Fusion Based on Multiscale Gradient Guided Edge-Smoothing Model and Local Gradient Weight

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成果类型:
期刊论文
作者:
Zou, Dengpeng;Yang, Bin;Li, Yuehua;Zhang, Xiaozhi;Pang, Lihui
作者机构:
[Li, Yuehua; Zhang, Xiaozhi; Zou, Dengpeng; Yang, Bin; Pang, Lihui] Univ South China, Coll Elect Engn, Hengyang 421001, Peoples R China.
语种:
英文
关键词:
Gradient guided filter (GF);local gradient weight;multiscale decomposition (MSD);visible (VS) and near-infrared (NIR) image fusion
期刊:
IEEE Sensors Journal
ISSN:
1530-437X
年:
2023
卷:
23
期:
3
页码:
2783-2793
基金类别:
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61871210, 62071213 and 61901209) 10.13039/501100009020-Chuanshan Talent Project of the University of South China Graduate Scientific Research Innovation Project of Hunan Province (Grant Number: CX20220984)
机构署名:
本校为第一机构
院系归属:
电气工程学院
摘要:
The visible (VS) and near-infrared (NIR) image fusion is a common approach to improve image visibility, which saves rich scene details and similar colors to the VS image in fused image. However, preserving edge details and preventing color distortion is a fundamental yet challenging problem for VS-NIR fusion work. To address this problem, this article proposes a novel image fusion method based on multiscale gradient guided edge-smoothing (MGES) model and local gradient weight. According to the spectrum characteristics of VS and NIR, the local gradient weight is established by analyzing the loc...

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