通过优化的变化模型去除遥感图像的剥离
Fei Yan1,2, Siyuan Wu1, Qiong Zhang1
1School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, China.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
这项研究引入了一种新的变化模型,用于从卫星遥感图像中去除水平条纹噪声. 该方法有效地消除噪音,同时保留精细的图像细节,优于现有技术.
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:
- 卫星图像中的条纹噪声降低了图像质量,并阻碍了应用程序.
- 现有的破坏方法经常导致细节丢失或引入文物.
研究的目的:
- 开发一种新的单向变化模型,以有效地消除水平条纹噪声.
- 通过保存图像细节和减少文物来改进现有方法.
主要方法:
- 一个单向变化模型,结合了条纹噪声的方向特征和结构稀疏性.
- 介绍了lp准规范,用于增强稀疏约束描述.
- 应用快速交替方向乘法 (ADMM) 来解决非形模型.
主要成果:
- 拟议的模型有效地消除了水平条纹噪声.
- 与现有方法相比,在保存精细图像细节方面表现出卓越的性能.
- 取得了优异的破坏效果,提高了效率和强度.
结论:
- 新的变化模型在卫星图像消毒方面取得了重大进展.
- 该方法提供了一种强大而有效的解决方案,可以消除条纹噪声,同时保持图像完整性.
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