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CDFAN:跨领域融合注意力网络,用于全面研磨

Jinting Ding¹, Honghui Xu², Shengjun Zhou³

¹School of Information and Electrical Engineering, Hangzhou City University, Hangzhou 310015, China.

Entropy (Basel, Switzerland)

|June 26, 2025

概括

一个新的跨域融合注意网络 (CDFAN) 通过使用高分辨率泛色数据来增强低分辨率的高光谱图像. 这种方法提高了空间质量和光谱保真度,优于现有的全磨技术.

科学领域:

遥感遥感遥感遥感
图像处理图像处理
计算机视觉计算机视觉

背景情况:

泛敏化通过使用高分辨率泛色彩 (PAN) 数据计算地提高了低分辨率超光谱图像 (LRMS) 的空间分辨率.
现有的方法在保护高频细节和有效整合空间光谱信息方面扎.

研究的目的:

引入一种新的架构,即跨域融合注意网络 (CDFAN),以改进全面利.
解决传统的空间域和基于频率的全化方法的局限性.

主要方法:

CDFAN使用一个多域交互注意 (MDIA) 模块,使用离散波波变换 (DWT) 来实现跨域的注意.
使用一个具有多尺度卷积路径和专家特征补偿器的空间多尺度增强 (SMCE) 模块.
注意力机制是跨波形和空间领域构建的,以实现有效的融合.

主要成果:

在基准数据集上,CDFAN显示出与最先进的全面利方法相比的显著改进.
拟议的网络在融合的高分辨率多光谱 (HRMS) 图像中实现了增强的光谱空间真实性.
结果显示出优越的重建质量和感知质量.

结论:

通过有效地整合多领域信息,CDFAN提供了一个强大的全面利解决方案.
该架构成功地保留了高频纹理和光谱完整性.
这一进步有助于为各种应用提供更高质量的高光谱图像融合.

关键词:

关注注意力注意力注意力注意力离散的波形变换.信息理论信息理论这是相互信息的互惠.整体研磨研磨机研磨机远程传感是一种遥感技术.

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