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Wavelet-based diffusion with spatial-frequency attention for hyperspectral anomaly detection
DOI:10.1016/j.jag.2025.104662.png)
摘要
En 中文
• 本文提出了一种基于小波的高光谱异常检测扩散模型。
• 本文结合了空间和频率双域特征。
• 本文引入了负对数似然噪声损失函数。
• 大量实验验证了其鲁棒性和跨域适应性。
Keyword:
Hyperspectral anomaly detection
Diffusion models
Wavelet transform
Remote sensing
期刊
IF:
8.6
论文数:
5.3K
被引数:
2.4W
机构
暂无机构信息
引用论文
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PATTERN RECOGNITION
IF7.6
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Hyperspectral Image Denoising via Tensor Low-Rank Prior and Unsupervised Deep Spatial-Spectral Prior基于张量低秩先验和无监督深空间光谱先验的高光谱图像去噪
Discriminative Reconstruction Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection用于高光谱异常检测的判别式重构约束生成对抗网络
Dictionary trained attention constrained low rank and sparse autoencoder for hyperspectral anomaly detection字典训练的注意力约束低秩稀疏自编码高光谱异常检测
NEURAL NETWORKS
IF6.3

