.png){kind=icon}
返回
SEQUENTIAL COVARIANCE CALCULATION FOR EXOPLANET IMAGE PROCESSING
.png){kind=icon}
OA
AI
DOI：10.1088/0004-637X/800/2/100.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Direct imaging of exoplanets involves the extraction of very faint signals from highly noisy data sets, with noise that often exhibits significant spatial, spectral, and temporal correlations. As a result, a large number of post-processing algorithms have been developed in order to optimally decorrelate the signal from the noise. In this paper, we explore four such closely related algorithms, all of which depend heavily on the calculation of covariances between large data sets of imaging data. We discuss the similarities and differences between these methods, and demonstrate how the use sequential calculation techniques can significantly improve their computational efficiencies.
Keyword:
methods: analytical
methods: numerical
techniques: image processing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.4
论文数:
8.3W
被引数:
32.0W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏分享收藏分享收藏Seroprevalence and risk factors for infection with equine coronavirus in healthy horses in the USAOAAI
OAAI分享收藏
查看更多内容