基于梯度一致性约束的无人机多光谱影像融合算法

doi:10.13229/j.cnki.jdxbgxb.20240525

Abstract

Abstract:

A UAV multispectral image fusion algorithm based on gradient consistency constraint was proposed to address the issues of multiple types of ground objects， difficulty in extracting features from UAV spectral images， and poor fusion performance caused by uncertain spectral information. By using the beam adjustment algorithm to ensure the consistency between the coordinates of ground points and the projected coordinates of images， and using wavelet transform to extract image features， combined with gradient consistency algorithm to construct the target fusion function， high-quality image fusion is achieved through iterative operation. Experimental results have shown that the fused image of this method has clear details， high resolution， and good information integrity， providing strong technical support for the subsequent application of unmanned aerial vehicle multispectral images， especially in the fields of environmental monitoring， agricultural evaluation， etc， it has shown broad application prospects.

Key words: remote sense, gradient consistency constraint, multi spectral imaging of drones, image fusion, local energy, edge gradient

CLC Number:

TP227

Yi TANG,Bing-chuan LU,Hong-chen YI,Cheng YU,Bin NAN. Multi spectral image fusion algorithm for unmanned aerial vehicles based on gradient consistency constraint[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(6): 2076-2081.

Figures/Tables 4

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参数名称	参数取值
影像大小	256×256
平均时间消耗/s	0.21
显色指数	95.2
辐射通量/MW	0.518
光效/（lm·W^-1）	79.26
无人机成像射线/nm	10⁴
成像点范围/mm	800~1 200

Multi spectral image fusion algorithm for unmanned aerial vehicles based on gradient consistency constraint

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