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PHoM:通过更高阶状态空间模型进行有效的全面化
Penglian Gao1, Hongwei Ge1, Shuzhi Su2
1Engineering Research Center of Intelligent Technology for Healthcare, Ministry of Education, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu, China; School of Artificial Intelligence and Computer Science, Jiangnan University, 1800 Lihu Avenue, Wuxi, 214122, Jiangsu, China.
这项研究引入了一种新的更高阶状态空间模型 (PHoM),用于泛化,增强多光谱图像分辨率. PHoM有效地模拟复杂的光谱特征相互作用,优于现有方法.
科学领域:
- 遥感 遥感 遥感 遥感
- 计算机视觉 计算机视觉
- 信号处理 信号处理
背景情况:
- 泛敏化从低分辨率的多光谱和高分辨率的泛色数据生成高分辨率的多光谱图像.
- 基于Mamba的模型在长距离关系建模方面表现出色,但在更高阶的光谱特征交互方面却扎不堪.
研究的目的:
- 提出一种新的更高阶状态空间模型 (PHoM) 用于面尖化.
- 为了增强光谱特征相互作用的建模,超出第一阶段映射.
- 为了提高对多光谱和泛色彩图像融合的表示能力.
主要方法:
- 引入了一个基于分割,交互和聚合的更高阶状态空间模型 (PHoM).
- 开发了一个交叉模式的PHoM以捕捉更高层次的交叉模式相关性.
- 在各种数据集上进行了广泛的实验,以验证性能.
主要成果:
- 拟议的PHoM有效地模拟了更高阶的空间适应性相互作用.
- 交叉模式的PHoM通过利用交叉模式的相关性来显著改善表示.
- 实验结果表明,与最先进的方法相比,性能大大提高.
结论:
- 通过解决模拟光谱特征相互作用的局限性,PHoM提供了一种优越的泛化方法.
- 跨模式扩展进一步增强了核聚变能力,从而产生了最先进的结果.
- 这项工作推进了高分辨率的多光谱图像生成技术.
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