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.     

Smear fitting: a new image-deconvolution method for interferometric data

A new technique is presented for producing images from interferometric data. The method, 'smear fitting', makes the constraints necessary for interferometric imaging double as a model, with uncertainties, of the sky brightness distribution. It does this by modelling the sky with a set of functions and then convolving each component with its own elliptical Gaussian to account for the uncertainty in its shape and location that arises from noise. This yields much sharper resolution than clean for significantly detected features, without sacrificing any sensitivity. Using appropriate functional forms for the components provides both a scientifically interesting model and imaging constraints that tend to be better than those used by traditional deconvolution methods. This allows it to avoid the most serious problems that limit the imaging quality of those methods. Comparisons of smear fitting to clean and maximum entropy are given, using both real and simulated observations. It is also shown that the famous Rayleigh criterion (resolution = wavelength/baseline) is inappropriate for interferometers as it does not consider the reliability of the measurements.     

图像减影技术在自动报靶系统中的应用

弹点分割一直是自动报靶系统的关健技术之一,所提出的减影技术不仅方法简单,而且能大大简化弹点的分割过程,使系统的工作效率明显地提高.     

利用小波变换进行遥感多光谱图像融合的算法及实现

在分析了小波变换的分解与重建方法后,提出了一种基于区域的图像增强算法。先提取出源图的边缘,以图像的边缘为参考,围绕边缘建立融合窗口,然后结合区域内的图像信息,应用基于窗口的融合规则进行融合处理。实验结果显示,融合后的图像综合了3幅源图像的不同特征,处理后的图像变得容易识别了。表明该方法保持了尽可能多的原始信息,算法简单,稳定性好,适合于多光谱遥感图像识别、医学成像等领域。     

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。     

Very Large Array observations of broad 6-cm excited-state OH lines in W49A

Using the Very Large Array (VLA), we observed all three of the 6-cm lines of the  ²Π_1/2, J = 1/2  state of OH with sub-arcsecond resolution (∼0.4 arcsec) in W49A. While the spatial distribution and the range in velocities of the 6-cm lines are similar to those of the ground-state (18-cm) OH lines, a large fraction of the total emission in all three 6-cm lines has large linewidths (∼5–10 km s⁻¹) and is spatially extended, very unlike typical ground-state OH masers, which typically are point-like at VLA resolutions and have linewidths ≤1 km s⁻¹. We find brightness temperatures of 5900, 4700 and ≥730 K for the 4660, 4750 and 4765-MHz lines, respectively. We conclude that these are indeed maser lines. However, the gains are ∼0.3, again very unlike the 18-cm lines, which have gains  ≥10⁴  . We compare the excited-state OH emission with that from other molecules observed with comparable angular resolution to estimate physical conditions in the regions emitting the peculiar, low-gain maser lines. We also comment on the relationship with the 18-cm masers.     

New confirmation of image-processing techniques for astrometry of Saturn and its satellites

The image-processing techniques used by Peng et al. are further improved to measure precisely the positions of Saturn and its satellites. 495 CCD images taken with the 1-m telescope at the Yunnan Observatory during the years 2002–2004 are processed with these techniques. These measured pixel positions are compared to their theoretical positions computed with the ephemerides of TASS1.7 for the satellites and JPL DE405 for Saturn itself. Analysis of the data for the intersatellite positions among four bright Saturnian satellites (S3–S6) and for Saturn–satellite (i.e. Saturn–Titan) positions shows that these measured positions have the same dispersions, i.e. about 0.05 and 0.06 arcsec in right ascension and declination, respectively. However, for the fainter satellites, Enceladus and Mimas, poorer residuals up to 0.1 and 0.2 arcsec, respectively, in both directions are found mainly due to their small separations from the primary planet and short exposure time in order to obtain useful images of Saturn.     

高挂山—牛头寨地区小型环形影象构造分析及其找矿意义

高挂山—牛头寨地区,通过大比例尺航片解译,发现6个大小不等的小型环形影象信息。这些环形影象与岩浆活动、已知矿床、矿化点、重砂异常、物化探异常等的分布有着内在的联系。为预测找矿远景区和找隐伏矿床提供了影象依据。     

APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO REMOTE SENSING*

Remote sensing is a geographic analysis tool capable of producing large quantities of data in the spectral, temporal and spatial domains. Techniques for automating the image analysis process would be advanced by the inclusion of artificial intelligence techniques in the design of image processing systems. The remote sensing application which show promise for successful implementation of artificial intelligence techniques are intelligent onboard processing, advanced database interrogation, and the automated analysis of multispectral imagery.     

Modelling and Mapping Damage to Forests from an Ice Storm Using Remote Sensing and Environmental Data

An extreme ice storm in January 1998 deposited up to 100 mm of ice and resulted in significant forest damage across eastern North America. Average crown loss of over 75% was recorded in large areas of eastern Ontario and southern Quebec. A primary question that arose following the storm was: can forest damage be effectively assessed using remote sensing and other available environmental data? This paper presents two contrasting studies to address this question. The first involves damage modelling at a local scale in an unmanaged forest using spectral and spatial information in high-resolution airborne imagery. Results of field data analyses are also given that show relations between damage and forest structure and composition as well as changes in forest structure that occurred in the years following the storm. The second study involves regional scale damage mapping in managed and unmanaged forests of eastern Ontario using medium resolution satellite imagery and other environmental data. In comparison of several image classification and data interpolation methods, the best damage map was produced using a neural network classifier and a mix of Landsat and environmental data. The methods and results presented in this paper form the basis for ongoing long-term temporal study of damage impacts on forest condition.