一种改进的车头SURF特征提取和匹配

通过对加速鲁棒性算法特征关键点提取和匹配的研究,提出一种改进的车头加速鲁棒性特征点提取方法,该方法在车头图像像素梯度变化较大的范围内提取关键点,然后采用最近邻比例算法进行特征点匹配。实验结果表明,提出的改进方法不仅能够筛选出鲁棒性较强的关键点,同时提高了特征的提取速度和匹配效率,在总时间上比尺度不变特征变换算法提高了3~6倍;比加速鲁棒性算法提高了近1/4。     

基于知识的遥感影像居民地信息提取——以山东省蓬莱市为例

如何自动获得居民地信息是遥感专题信息提取研究的热点问题,该文以山东省蓬莱市为研究区,基于对2004年TM影像光谱特征的分析,建立了基于知识的居民地信息自动提取模型,并对提取结果进行了精度评价。结果表明,利用该模型可以很好地将蓬莱地区的城镇居民地自动提取出来,其提取精度与传统的监督分类方法相比有了很大提高。     

Few projections astrotomography: radio astronomical approach to 3D reconstruction

We develop a radio astronomical approach to 3D‐reconstruction in few projections tomography. It is based on the 2‐CLEAN DSA method which consists of two clean algorithms by using a synthesized beam. In complex cases two extreme solutions are used for the analysis of the image structure. These solutions determine the limits of permissible energy redistribution on the image among the components of small and large scales. Two variants of 3D‐reconstruction proceeding from a set of two‐dimensional projections (3D_2D) and from a set of one‐dimensional ones (3D_1D) are considered. It is shown that the quality of 3D_2D‐reconstruction should be similar to the quality of 2D_1D‐reconstruction if the same number of equally spaced scans is used. But a doubled number of projections is required for 3D_1D‐reconstruction. We have simulated 3D‐reconstruction of an optically thin emitting object. The present technique is a component of astrotomography and it has good prospects for a wide range of remote sensing. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

紫金山天文台赣榆观测站精细结构望远镜终端系统改造及最新观测结果

为了观测太阳耀斑高速电子轰击色球,紫金山天文台赣榆观测站将原精细结构望远镜改造为高速CCD精细结构望远镜,拍摄到局部H_α活动区．在光学系统里增加缩焦器,引进干涉偏振滤光片后,高速CCD就能记录H_α各波段的单色像．经过1999年至2004年的反复试验和改进,目前H_α图像的空间分辨率己达1个角秒,时间分辨率为每秒钟30至40帧图像．2004年11月观测到一个M1．1级耀斑,我们将H_α紫移(H_α-0．5(?))高速图像和硬X-射线暴、射电微波暴比较,结果发现：初始的耀斑成对亮点在上升相相互靠近,特别是微波暴源也显出类似的靠近运动,以前从未观测到这种现象,它可解释为磁弧脚根沿中性线的剪切运动．     

实时相关跟踪图像处理系统

文章介绍了怀柔太阳观测基地最近完成的一套实时高分辨太阳磁场观测系统。系统采用局部相关跟踪算法来提高磁场观测数据的空间分辨率，同时对相关跟踪算法的实现程序进行了优化以满足常规太阳磁场观测的要求。通过对试观测和常规观测数据的分析，我们发现：1）该系统能够大大提高单色像、磁场数据的对比度和空间分辨率；2）对相关跟踪算法的优化大大提高了系统的时间分辨率，系统可以投入常规观测使用。     

Research on Parallel Algorithms for uv-faceting Imaging

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.     

Application of an adaptive filtering technique to surface photometry of galaxies. I. The method tested on NGC 3379

This study reports on the results of the application of an adaptive filtering technique to the two-dimensional photometric mapping of galaxies. For this test we used the elliptical galaxy NGC 3379, which is a luminosity standard. Our plate material (B-band), obtained with the Tautenburg Schmidt telescope, was digitized with the Babelsberg microdensitometer and with the ESO PDS. The 2-D scans were reduced according to the Babelsberg Image Processing Systems, whose key feature is an adaptive filter called ‘H-Transform’. By comparing our results (E-W light profile and isophotal parameters) to the most recent studies of NGC 3379 (DE VAUCOULEURS and CAPACCIOLI 1979, and NIETO and VIDAL 1984), we found no systematic errors in the photometric calibration and in the reduction procedure, with typical mean residuals from the other studies not larger than ±0.05 B-mag up to a threshold of 1% of the night sky level on each plate. We also re-confirmed the geometrical properties of the galaxy. The new filtering technique proved quite efficient in reducing the noise, with negligible effects on the photometric and geometric characteristics of the star-like sources.     

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

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.     

Fast compression and reconstruction of astronomical images based on compressed sensing

With the fast increase in the resolution of astronomical images, the question of how to process and transfer such large images has become a key issue in astronomy. We propose a new real-time compression and fast reconstruction algorithm for astronomical images based on compressive sensing techniques. We first reconstruct the original signal with fewer measurements, according to its compressibility. Then,based on the characteristics of astronomical images, we apply Daubechies orthogonal wavelets to obtain a sparse representation. A matrix representing a random Fourier ensemble is used to obtain a sparse representation in a lower dimensional space. For reconstructing the image, we propose a novel minimum total variation with block adaptive sensing to balance the accuracy and computation time. Our experimental results show that the proposed algorithm can efficiently reconstruct colorful astronomical images with high resolution and improve the applicability of compressed sensing.     

Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.