An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest     

《Chinese Astronomy and Astrophysics》2020,44(1):41-60

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   

基于CUDA的地震相干体并行算法   总被引：1，自引：0，他引：1  

张全 《地质与勘探》2020,56(1):147-153

相干体技术在地震勘探资料解释方面得到了广泛的应用,由于相干体技术处理的对象是三维地震数据体,所以算法运算时间较长。为了缩短解释周期,本文充分发挥GPU并行计算优势,对C3相干体算法进行并行化分析。从硬盘读取数据到GPU上计算相干值并写入硬盘的整个过程进行分析,剔除了冗余数据的读取,完成了C3相干体算法的并行化设计与实现。最后分别对串行算法与并行算法进行性能测试,结果表明本文设计的并行算法在保证精度的前提下达到了16倍左右的加速比,对加快地震资料解释具有重要意义。  相似文献   

Research on Parallel Algorithms for uv-faceting Imaging     

《Chinese Astronomy and Astrophysics》2019,43(3):424-443

The uv-faceting imaging is one of the widely used large field of view imaging technologies, and will be adopted for the data processing of the low-frequency array in the first stage of the Square Kilometre Array (SKA1). Due to the scale of the raw data of SKA1 is unprecedentedly large, the efficiency of data processing directly using the original uv-faceting imaging will be very low. Therefore, a uv-faceting imaging algorithm based on the MPI (Message Passing Interface)+OpenMP (Open Multi-Processing) and a uv-faceting imaging algorithm based on the MPI+CUDA (Compute Unified Device Architecture) are proposed. The most time-consuming data reading and gridding in the algorithm are optimized in parallel. The verification results show that the results of the proposed two algorithms are basically consistent with that obtained by the current mainstream data processing software CASA (Common Astronomy Software Applications), which indicates that the proposed two algorithms are basically correct. Further analysis of the accuracy and total running time shows that the MPI+CUDA method is better than the MPI+OpenMP method in both the correctness rate and running speed. The performance test results show that the proposed algorithms are effective and have certain extensibility.  相似文献   

基于卷积神经网络与条件随机场方法提取乡镇非正规固体废弃物     

刘懿兰  黄晓霞  李红旮  柳泽  陈崇  王新歌 《地球信息科学学报》2019,21(2):259-268

随着村镇经济建设发展,生活垃圾和工业固体废弃物造成的污染问题日益突出,已经成为制约新农村建设发展和生态文明建设的关键问题,而目前针对乡镇非正规固体废弃物的调查与统计主要依赖全国各乡镇相关部门逐级调查上报,工作量较大。本文基于高分辨率遥感影像,将深度学习模型和条件随机场模型相结合引入到乡镇固体废弃物的提取研究中,探索一种基于深度卷积神经网络的乡镇固体废弃物提取模型。由于固体废弃物在影像上表现为面积小,分布破碎等特点,为了提高工作效率,将模型特分为识别和提取2个部分：① 通过全连接卷积网络（CNN）对固体废弃物进行快速识别判断,筛选感兴趣区域影像块;② 在传统的全卷积神经网络(FCN)的基础上加入条件随机场模型(CRF)提取固体废弃物边界,提高整体分割精度。根据安徽、山西等地区相关部门上报固体废弃物堆放点以及住房与城乡建设部城乡规划管理中心进行野外检查的结果,实验最终识别精度达到86.87%以上;形状提取精度为89.84%,Kappa系数为0.7851,识别与提取精度均优于传统分类方法。同时,该方法已经逐步应用于住房和城乡建设部有关成都、兰州、河北等部分乡镇非正规固体废弃物的核查工作,取得了较为满意的结果。  相似文献   

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements     

Yingjie Hu  Huina Mao  Grant McKenzie 《International journal of geographical information science》2019,33(4):714-738

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.  相似文献   

基于小波变换的射频干扰消除方法的研究          下载免费PDF全文

林天琪  吴亚军  朱人杰  徐志骏 《天文学报》2021,62(3):29

在射电天文观测中,射频干扰(Radio Frequency Interference, RFI)会以多种形式混入望远镜接收系统,给观测带来误判或者降低观测信噪比.近年来国内国际射电天文快速发展,国内国际大型射电望远镜和阵列先后建设,观测灵敏度大为提高,射频干扰的影响尤为突出.随着科技发展和人类活动的加剧,射频干扰日益严重且不可逆转.提出利用2维离散小波变换的方法分析射电天文观测的数据,对望远镜系统输出的时间频率序列进行小波变换,根据小波系数分离出原始信号中各分量,每个分量统计得到相应的阈值,将各分量与阈值相比较识别干扰成分并标记去除.利用该方法对实际观测数据进行了处理,结果表明该方法能够很好地标记并消减干扰信号,且提高了观测的信噪比.  相似文献   

Research on the Application of Fast-steering Mirror in Stellar Interferometers     

Mei Rong  Hu Zhong-wen  Xu Teng  Sun Chang-sheng 《Chinese Astronomy and Astrophysics》2018,42(3):475-486

In stellar interferometers, the fast-steering mirror (FSM) is widely utilized to correct the wavefront tilt caused by the atmospheric turbulence and internal instrumental vibration, because of its high resolution and fast response frequency. In this study, the non-coplanar error between the FSM and the actuator deflection axis introduced by the manufacturing, assembly, and adjustment is analyzed systematically. Via a numerical method, the additional optical path difference (OPD) caused by the above factors is studied, and its effect on the fringe tracking accuracy of a stellar interferometer is also discussed. On the other hand, the starlight parallelism between the beams of two arms is one of the main factors for the loss of fringe visibility. By analyzing the influence of wavefront tilt caused by the atmospheric turbulence on fringe visibility, a simple and efficient real-time correction scheme of starlight parallelism is proposed based on a single array detector. The feasibility of this scheme is demonstrated by a laboratory experiment. The results show that after the correction of fast-steering mirror, the starlight parallelism meets preliminarily the requirement of a stellar interferometer on the wavefront tilt.  相似文献   

顾及地形起伏的无人机影像覆盖分析方法     

张衡  李骁  叶朋飞 《测绘通报》2020,(1):102-106

使用无人机实施测绘航空摄影时，由于无人机相对航高较低，地面起伏会对无人机影像的分辨率、覆盖范围、重叠度造成较大的影响，影像成果会出现分辨率不足、重叠度不够、覆盖漏洞等缺陷。针对这一情况，本文提出了一种利用数字微分正解法的计算方法，借助DEM准确计算每张影像的覆盖范围，并使用FME软件高效生成全部影像的覆盖范围。经过实际使用，验证了该方法可以在航线设计阶段准确预测并分析全部影像的覆盖范围、重叠度，因此可及时发现设计问题并调整航线。该方法可以有效减少因地形起伏造成的影像覆盖缺陷，减少返工现象，从整体上提高了作业效率。  相似文献   

结合图像增强和恢复的增强现实跟踪注册     

郭士祥  范铀  范冲 《测绘通报》2020,(8):39

增强现实中的跟踪注册技术一直是研究的重点和难点，而地下矿道和巷道内亮度低，产生的图像较昏暗，车载相机快速运动和抖动，对传统的基于特征匹配的跟踪注册提出了挑战。本文从提高增强现实中跟踪注册稳健性和精度出发，采用基于Retinex改进的方法增强昏暗图像的亮度，同时利用基于对抗神经网络的方法恢复运动模糊图像。首先提取图像ORB特征，实现初始化；然后根据跟踪特征点的数量，开启图像增强和图像恢复线程，提高特征点提取质量和数量。在数据集和真实模拟场景下的试验结果显示，跟踪精度提高了12%左右，在低亮度和含有轻微模糊的情况下，跟踪注册稳健性也有显著提高。  相似文献   

基于深度学习理论的无人机影像分类     

阳成 《北京测绘》2020,(4):481-484

针对无人机影像深度学习分类方法缺乏现状,本文利用深度学习理论卷积神经网络方法对无人机影像进行了分类。该法首先抽取无人机影像作为训练集和检验集,然后建立一个2个卷积层-池化层的卷积神经网络模型进行深度学习,通过设定参数并运行模型实现无人机影像分类。实验表明,本文提出的方法可完成较复杂地区无人机影像分类,其分类精度与支持向量机方法相当,为无人机遥感影像分类提供了一个崭新的技术视点。  相似文献