多功能天文经纬仪图像处理系统

多功能天文经纬仪是云南天文台新研制的一种基于通用CCD观测的天体测量望远镜。介绍了多功能天文经纬仪的图像处理系统,从系统的整体框架和主要功能算法两个方面说明了整个图像处理系统的实现流程和工作方法。介绍了星像搜索算法、定心算法和VC＋＋程序设计的流程图。给出了图像处理软件的界面,以及恒星像、人造星像和轴准直星像3种星像的定心结果,并对其结果进行了分析。     

基于有效点扩散函数的高精度测光

介绍了利用有效点扩散函数拟合方法得到CCD图像中恒星仪器星等的过程。对国家天文台1 m望远镜观测的16幅CCD图像进行实际测量,结果表明:亮星的内部测量平均精度为0.015 mag,最高精度可达0.001 5 mag,而暗星则达到0.043 mag。与Gauss拟合测光方法相比平均精度提高了3倍多,精度标准偏差是0.005,说明该测量方法比较稳定,是一种更优的测光方法。     

矮行星Haumea系统定心算法的探究

受地球大气影响, 使用地基光学望远镜观测角距离较小的双星系统或主卫星系统时往往会出现星象不可分辨的情况. 因此, 系统光心位置与系统质心位置可能存在一定的偏差. 准确地测量太阳系天体系统质心位置可以改进其轨道参数, 有助于揭示太阳系的形成与演化. 以矮行星Haumea及其亮卫星Hiíaka的运动为例, 仿真系统光心围绕质心扰动的过程, 探究视宁度(用星象的半高全宽表示)变化对准确测量光心位置的影响. 仿真结果表明, 使用二维高斯定心算法测定的系统光心位置随视宁度变化, 而修正矩定心算法的定心结果不受视宁度的影响. 根据仿真结果, 研究能够有效减少视宁度变化对光心位置准确测量影响的定心算法十分必要; 同时, 新的定心算法还需考虑主星光度变化的影响. 使用云南天文台2.4m望远镜, 1m望远镜以及紫金山天文台姚安观测站0.8m望远镜从2022年2月7日至2022年5月25日观测矮行星Haumea系统, 得到29晚共463幅CCD图像. 新定心算法确定的光心位置与使用二维高斯定心算法的结果相比具有更好的位置拟合效果. 此外, 还发现亮卫星Hiíaka在Jet Propulsion Laboratory (JPL)历表与Institut de Mécanique Céleste et de Calcul des ''Ephémérides (IMCCE)历表中的位置存在较大偏差.     

机器视觉高斯拟合法自动导星定心系统设计

丽江2.4m光学望远镜自动导星系统升级改造需要计算CCD图像中实际星像中心的位置,在现有导星定心算法的基础上,利用机器视觉Canny边缘检测和椭圆拟合的方法识别星像轮廓,然后对星像直接二维高斯拟合,计算星像中心位置.研究了导星算法中涉及的天光背景参数、星像轮廓识别所需阈值、星像拟合边界参数的整定方法,总结出有效的自动导星定心方法,并开发了基于Linux平台的高速自动导星定心系统软件.软件对星像的高斯拟合结果与IRAF软件高斯拟合结果一致;同一天区相邻时间图像中星像中心偏移量计算结果也表明算法的有效性.     

光子计数资料处理方法的比较

本文通过对天体测量仪器光子计数模拟资料的处理,比较了13种不同的平滑模型和两种定心算法对最终精度的影响;提出了利用频率域滤波和修正矩方法相结合的最佳处理方法;并对比较结果进行了多方面的讨论。     

ePSF拟合法与Gaussian拟合法的比较

为了解决哈勃空间望远镜的图像欠采样问题,美国学者Anderson和King提出了精确测量星像位置和通量的有效点扩散函数(ePSF—effective point-spread function)拟合法。然而,他们却不加比较地将其应用于地面CCD图像中星像的位置高精度测量。因此,我们试图将ePSF拟合法与经典的高斯函数(Gaussian)拟合法作比较研究。调用CFITSIO库生成模拟的背景图像,并应用不同参数条件下的星像轮廓模型产生非欠采样的星像。最后,分别采用ePSF拟合法与Gaussian拟合法对这些星像进行拟合,并对它们的拟合精度进行比较。实验结果表明,在非欠采样的图像中这两种算法对星像位置的测量几乎是等精度的。     

天王星卫星两种定标方法测定结果的比较

利用新发表的高精度、高密度天体测量星表UCAC2,对天王星的五颗主要卫星的CCD观测图像重新进行量测,采用不同方法作定标归算,并使用两种理论模型(GUST86和GUST06模型)计算卫星的理论位置。对不同方法所得到的卫星位置的O-C结果的分析和比较表明,本文获得的卫星位置精度,除天卫五(Miranda)有显著提高,其他4颗卫星的位置精度基本相同。本文中天卫一和天卫三的结果与"亮卫星定标法"的结果在精度上相当,天卫二的位置精度与其他天王星卫星的位置精度具有较好的一致性,这从另一方面证明了我们的"亮卫星定标法"的可靠性。此外我们还获得了天卫四的位置与精度。     

CCD图像拼接试验

为了获得大视场的高精度天文图像,实施了一种望远镜CCD图像的拼接方法。从原始图像到最终合成图像的坐标转换采用了结合星表UCAC4的六常数模型。不同于硬件级的拼接,使用逐个像素的灰度值再分配的方案进行图像融合。进一步采用云南天文台2.4 m望远镜拍摄的CCD图像进行了试验。结果表明,该算法可以产生较高质量的大视场CCD图像,可以直观地发现运动目标,暗星信噪比有显著改善。高精度的图像拼接还与原始数据扭曲改正的预处理密不可分。与未做扭曲改正相比,图像拼接的位置精度提高了约一倍(约0.02 pixel)。     

天然卫星CCD精确定位的最新进展

天然卫星CCD精确定位观测对于宇宙飞船探测外行星、行星物理的研究以及天文参考系的连接等方面都有重要的意义．文章介绍了长焦距望远镜CCD观测天然卫星所遇到的各种困难以及解决问题的方案．重点评介了CCD图像处理和归算方法．最后,介绍了影响天然卫星位置测量精度的各种因素及最新观测结果的精度．     

DCMT枢轴误差的光电测定

枢轴误差是影响天体位置测量精度的重要因素.对于现代子午环的高精度天体测量而言,枢轴误差的精确测定是必不可少的.利用DCMT的自校准光源的像,并采用V形光栅的光电扫描直接测定DCMT枢轴误差在赤经和赤纬上的分量。通过几次测量结果的比较表明,该方法具有很高的测量精度与重复性.     

CCD图像的二维修正矩定心方法

对于天体测量而言，ＣＣＤ图像的数字星像处理方法是十分重要的．本文根据ＣＣＤ器件的特性，从理论上推导了二维修正矩算法的最佳门限取值方法．通过处理模拟和实测数据，与传统的二维高斯拟合法比较，在保持矩方法简便特性的同时，在精度上亦有所提高，对于暗星效果更为明显．     

Matching CCD images to a stellar catalog using locality-sensitive hashing

The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.     

基于CCD星图的空间目标精确光学定位方法研究

通过光学定位方法来确定空间目标的轨道是实现空间目标监测的重要手段之一。介绍一套小型的空间目标光学定位系统,针对该系统获取的CCD星图,提出Top-hat变换和中值滤波相结合的算法去除星图噪声,并提出基于梯度Hough变换的算法完成对CCD星图星点和轨迹的同时精确定位,最后利用星角距的旋转不变性和球面几何原理,实现对空间目标的精确定位。对分辨率为752×580的CCD实拍星图的应用研究结果表明,星图去噪算法和星点、轨迹同时精确定位算法是有效的,且空间目标的定位精度也可达到角秒量级。     

两种快速星像匹配算法的比较

星像的位置和亮度等信息对天文研究和空间导航具有基础意义。人们常常需要快速匹配从密集星场CCD图像中提取的信息来获取与星表中对应的信息(如位置、光度等),因此开发出了多种星像匹配算法。重点比较了两种最新的星像匹配算法:i)基于向量的方法;ii)基于径向和环向特征的方法。通过对云南天文台1m望远镜观测的CCD图像进行实际匹配,结果表明基于向量的方法更优,它是一种快速的、接近常数时间的匹配算法。     

同幅双速跟踪成像CCD相机模拟电路系统设计

讨论了同幅双速跟踪成像技术对CCD相机系统的特殊要求,详细地介绍了该相机前端模拟系统的设计思想、系统结构和主要的电路模块。对系统中一些关键电路模块进行了仿真和测试,并对仿真和测试结果进行比较分析,以检验电路系统设计的合理性。     

研制低纬子午环初衷的沿革

介绍了在低纬子午环研制过程中，如何跟踪国内外测量方法和科学技术的发展，调整该仪器的主要课题目标：开始时仅计划在低纬度地区进行天体位置的绝对测定，改善基本星表系统；在１ｍ望远镜试验ＣＣＤ底片重迭法成功后，打算把该仪器绝对测定的恒星位置与河外天体联系起来，间接地建立准惯性天球参考架；当国外传统子午环配备ＣＣＤ测微器作相对测量后，提出了在该仪器上配备ＣＣＤ测微器作绝对测定的方法，用其观测数据直接建立实用的准惯性天球参考架，并为太阳系和银河系研究提供有用数据的总体目标。     

Fast Object Detection for Use Onboard Satellites

We propose an object detection algorithm which is efficient and fast enough to be used in (almost) real time with the limited computer capacities onboard satellites. For stars below the saturation limit of the CCD detectors it is based on a four neighbourhood local maximum criterion in order to find the centre of a stellar image. For saturated stars it is based on the assumption that the image is increasing monotonically towards the centre in the unsaturated part of the image. The algorithm also calculates approximate stellar magnitudes and efficiently rejects most of the cosmics which would otherwise lead to a large number of false detections. The quality of the algorithm was evaluated with the help of a large set of simulated data for the DIVA satellite mission; different assumptions were made for the noise level, and the presence of cosmics or for a variable sky background.We could show that our algorithm fulfills the requirements for DIVA; only in the case of simulated images which included the bright galaxy M31 some fainter stars could not be detected in the galaxy's vicinity. Since stellar images contain large areas without any stars, we propose an additional block-skipping algorithm which can be coded on special-purpose hardware. This revised version was published online in July 2006 with corrections to the Cover Date.     

Removing cosmic-ray hits from CCD images in real-time mode by means of an artificial neural network

A feed-forward artificial neural network has been implemented to the problem of removing cosmic-ray hits (CRH) from CCD images. The results of a number of tests demonstrate the effectiveness of this method especially for undersampled stellar profiles. The problem of optimal and low price preparing of training data, which could enable real-time or at least fast post-processing filtering out of CRH is discussed. The training and test ensembles were composed of a number of synthetic stellar profiles involving different S/N ratios and CRH images taken from real data. Certain aspects of the network’s architecture and its training efficiency for different modes of the back-propagation procedure as well as for the pre-process normalization of data have been examined. It is shown that for training set composed of stellar images and CRH at a ratio of 1:2 recognition can reach 99% in the case of stars and 96% for CRH. To determine the extent to which the cognition power of a network trained using an ensemble of circular symmetric stellar profiles of a given radius can be generalised the test data included stellar profiles of different radii, as well as elongated profiles. The goal was to mimic temporal changes in seeing as well as such problems as image defocusing, the lack of isoplanatism and improper sideral tracking of a telescope. The experiments provided us with the conclusion that for S/N > 10 excellent classification property is maintained in cases where the change in the radius of a circular profile is up to 30%, as well as for elongated profiles where the longest dimension is almost double that of the shortest one. Moreover, the generalization capability has been investigated for test images of synthetic pairs of overlapping stars with different distances between components. Almost 99% recognition efficiency was achieved even if the separation was nearly three times the radius of the stellar profile, a case when two stars could be analyzed by appropriate software as separate objects. The example of removal of CRH from real CCD images is presented to give an idea of how an algorithm based on a neural network can work in practice. The result of such an experiment appears fully consistent with the conclusions drawn from the tests made on synthetic data.     

A new segmentation algorithm for lunar surface terrain based on CCD images

Terrain classification is one of the critical steps used in lunar geomorphologic analysis and landing site selection. Most of the published works have focused on a Digital Elevation Model(DEM) to distinguish different regions of lunar terrain.This paper presents an algorithm that can be applied to lunar CCD images by blocking and clustering according to image features, which can accurately distinguish between lunar highland and lunar mare. The new algorithm, compared with the traditional algorithm, can improve classification accuracy. The new algorithm incorporates two new features and one Tamura texture feature. The new features are generating an enhanced image histogram and modeling the properties of light reflection, which can represent the geological characteristics based on CCD gray level images. These features are applied to identify texture in order to perform image clustering and segmentation by a weighted Euclidean distance to distinguish between lunar mare and lunar highlands.The new algorithm has been tested on Chang'e-1 CCD data and the testing result has been compared with geological data published by the U.S. Geological Survey. The result has shown that the algorithm can effectively distinguish the lunar mare from highlands in CCD images. The overall accuracy of the proposed algorithm is satisfactory, and the Kappa coefficient is 0.802, which is higher than the result of combining the DEM with CCD images.     

Problems of CCD Photometry of Fast-Moving Asteroids

The problems associated with the photometry of fast-moving asteroids are discussed. The effect of noise in CCD observations on the photometric accuracy is analyzed. A photometric accuracy limitation is shown to exist for observations of asteroids, which is determined by the angular rate of the object and the ratio of the flux from the object and noise due to sky background and dark current. The effective exposure for observing a moving object is determined. The method of overlapping areas is analyzed, which is used for obtaining the lightcurves of fast-moving asteroids. This method includes the determination of the mutual magnitude differences for the entire ensemble of comparison stars, the reduction of the magnitudes of all these stars to the magnitude of one of them adopted as the primary comparison star, the determination of the magnitude of the average star on each frame of the entire series of CCD observations, and the computation of the lightcurve as the difference between the magnitude of the asteroid and that of the average star.