用图像配准与盲反卷积修复大气湍流造成的模糊图像

Atmospheric turbulence restoration by diffeomorphic image registration and blind deconvolution

• 结合盲反卷积与弹性配准，分步恢复湍流扭曲图像
• 在新墨西哥沙漠实测数据上显著提升图像清晰度
• 适合从事图像复原、天文观测或遥感成像的研究者

本文提出一种新方法，用于改善受大气湍流影响的图像质量。基于盲反卷积模块、弹性配准模块和时序滤波模块的两种组合，设计了两种新算法。这些算法在北约RTG40小组于新墨西哥沙漠采集的真实图像上进行了测试，有效提升了图像清晰度，验证了其在复杂湍流条件下的实用性。

原文摘要 · Abstract (English)

A novel approach is presented in this paper to improve images which are altered by atmospheric turbulence. Two new algorithms are presented based on two combinations of a blind deconvolution block, an elastic registration block and a temporal filter block. The algorithms are tested on real images acquired in the desert in New Mexico by the NATO RTG40 group.

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。