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题名: Blind deconvolution with principal components analysis for wide-field and small-aperture telescopes
作者: Jia, Peng; Sun, Rongyu; Wang, Weinan; Cai, Dongmei; Liu, Huigen
刊名: MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
出版日期: 2017
卷号: 470, 期号:2, 页码:1950-1959
英文摘要: Telescopes with a wide field of view (greater than 1 degrees) and small apertures (less than 2 m) are workhorses for observations such as sky surveys and fast-moving object detection, and play an important role in time-domain astronomy. However, images captured by these telescopes are contaminated by optical system aberrations, atmospheric turbulence, tracking errors and wind shear. To increase the quality of images and maximize their scientific output, we propose a new blind deconvolution algorithm based on statistical properties of the point spread functions (PSFs) of these telescopes. In this new algorithm, we first construct the PSF feature space through principal component analysis, and then classify PSFs from a different position and time using a self-organizing map. According to the classification results, we divide images of the same PSF types and select these PSFs to construct a prior PSF. The prior PSF is then used to restore these images. To investigate the improvement that this algorithm provides for data reduction, we process images of space debris captured by our small-aperture wide-field telescopes. Comparing the reduced results of the original images and the images processed with the standard Richardson-Lucy method, our method shows a promising improvement in astrometry accuracy.
语种: 英语
内容类型: 期刊论文
URI标识: http://libir.pmo.ac.cn/handle/332002/17362
Appears in Collections:空间目标与碎片观测研究基地_期刊论文

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