论文标题
一种用于幸运成像的新型混合算法
A Novel Hybrid Algorithm for Lucky Imaging
论文作者
论文摘要
Lucky Imaging是一种具有两种经典实现算法的高分辨率天文图像恢复技术,即在傅立叶空间中选择,移动和添加图像空间以及数据选择和图像合成的图像。本文提出了一种新颖的幸运成像算法,其中以空间域和频域的选择率作为链接,两种经典算法成功地结合在一起,使每种算法成为新型混合算法的适当子集。实验结果表明,在相同的实验数据集和平台中,提出的算法获得的高分辨率图像优于通过两种经典算法获得的高分辨率图像。本文还提出了一种新的幸运图像选择和存储方案,该方案可以极大地节省计算机内存,并使Lucky Imaging算法可以在带有较小内存的通用台式机或笔记本电脑中实现,并处理具有更多框架和更大尺寸的天文图像。此外,通过仿真分析,本文讨论了在不同大气条件下新型幸运成像算法和传统算法的二进制恒星检测极限。
Lucky imaging is a high-resolution astronomical image recovery technique with two classic implementation algorithms, i.e. image selecting, shifting and adding in image space and data selecting and image synthesizing in Fourier space. This paper proposes a novel lucky imaging algorithm where with space-domain and frequency-domain selection rates as a link, the two classic algorithms are combined successfully, making each algorithm a proper subset of the novel hybrid algorithm. Experimental results show that with the same experiment dataset and platform, the high-resolution image obtained by the proposed algorithm is superior to that obtained by the two classic algorithms. This paper also proposes a new lucky image selection and storage scheme, which can greatly save computer memory and enable lucky imaging algorithm to be implemented in a common desktop or laptop with small memory and to process astronomical images with more frames and larger size. Besides, through simulation analysis, this paper discusses the binary star detection limits of the novel lucky imaging algorithm and traditional ones under different atmospheric conditions.