Substitution of satellite-based land surface temperature defective data using GSP method

Land surface temperature (LST) as an important environmental variable provides valuable information for earth environmental system modelling. Currently, LST is obtained through satellite thermal sensors at various spatial and temporal resolutions. Although spatially continuous satellite-based LST measurements are intended to overcome the shortcomings of sparse ground-based LST measurements, LST images often contain anomalous values due to the existence of clouds or sensor malfunctioning. The problem becomes more serious where the users deal with high spatial resolution characterized by low temporal resolution. This study examines the capability of a newly developed graph signal processing (GSP) method using two-dimensional single-date thermal data. For this purpose, four Landsat/TIRS datasets are analyzed. The data of five elliptical regions on thermal images are eliminated and then reconstructed through the GSP method and using the LST values of the enclosing rectangles containing the ellipsoids. The results indicate that the temperature variation determined by the GSP method generally conforms to the original image LST values. According to a correlation test conducted on the original image LST and those obtained through the GSP method, the values vary from 58% to 95%, which is an above-the-average rate (RMSE from 0.69 to 2.27). The statistical analysis of the original image LST in both the elliptical regions and the enclosing rectangles containing the ellipsoids indicates that an increase in the variance of LST data causes an increased error in the calculation of temperature by the GSP method, and vice versa. The results of the analysis of variance (ANOVA) and Duncan test indicated that an increase in the number of the non-zero spectral bins would result in increased RMSE values for all the dates and the regions. Moreover, the model errors were significant at the 0.05 level across all the image date and five elliptical study regions. Based on the results, the use of this method is recommended for the reconstruction of LST missing values, where dissimilarity of atmospheric conditions limits the use of other methods that depend on the time series data of various dates and a great deal of data calculation.     

Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

Obscured Activity: AGN, Quasars, Starbursts and ULIGs Observed by the Infrared Space Observatory

Some of the most ‘active’ galaxies in the Universe are obscured by large quantities of dust and emit a substantial fraction of their bolometric luminosity in the infrared. Observations of these infrared luminous galaxies with the Infrared Space Observatory (ISO) have provided a relatively unabsorbed view to the sources fuelling this active emission. The improved sensitivity, spatial resolution and spectroscopic capability of ISO over its predecessor Infrared Astronomical Satellite (IRAS) of enabled significant advances in the understanding of the infrared properties of active galaxies. ISO surveyed a wide range of active galaxies which, in the context of this review, includes those powered by intense bursts of star formation as well as those containing a dominant active galactic nucleus (AGN). Mid-infrared imaging resolved for the first time the dust enshrouded nuclei in many nearby galaxies, while a new era in infrared spectroscopy was opened by probing a wealth of atomic, ionic and molecular lines as well as broad band features in the mid- and far-infrared. This was particularly useful, since it resulted in the understanding of the power production, excitation and fuelling mechanisms in the nuclei of active galaxies including the intriguing but so far elusive ultraluminous infrared galaxies. Detailed studies of various classes of AGN and quasars greatly improved our understanding of the unification scenario. Far-infrared imaging and photometry revealed the presence of a new very cold dust component in galaxies and furthered our knowledge of the far-infrared properties of faint starbursts, ULIGs and quasars. We summarise almost nine years of key results based on ISO data spanning the full range of luminosity and type of active galaxies.     

基于磁场映像的印制电路板故障诊断方法研究

简要分析了印制电路板的电磁场，提出了用电磁感应法测量磁场的电咱故障诊断新方法，并给出了测试系统组成方案。最后通过验证实验证明了该方法是确实可行的。     

弹道靶红外辐射测量

为深入认识再入物理现象 ,在弹道靶上做了模型头部和近尾流红外辐射测量。发射器为 1 4.5mm口径的二级轻气炮 ,模型为1 0mm的球 ,材料为聚碳酸酯和铝 ,模型发射速度 4～6km/s,使用红外InSb探测器测量波长 3～ 5 .4μm的红外辐射 ,靶室压力 5 .32kPa。实验中使用光电法测量模型速度 ,两站阴影照相进行模型姿态监测和速度核实。实验结果表明 :球模型的红外辐射强度强烈依赖于模型材料和模型飞行速度。对不同材料模型头部和尾流部辐射强度的定性比较说明由于低温材料烧蚀产物的存在 ,极大地增强了头部和近尾流区的辐射强度 ,而且延长了尾流辐射长度     

提高图像轮廓清晰度的快速插值放大方法

分析了当前主要的高清晰度图像插值放大方法,为实现快速放大而选择了基于图像轮廓插值改善清晰度的技术路线,并在已有算法的基础上开展了进一步的研究.提出了新的图像轮廓线光顺数值算法,对轮廓线划分的两类子区域提出了精度更高的插值算法.最后,以典型平面图形的图像和由3DMax生成的三维渲染图像为例对本文方法进行检验,与双线性插值结果的对比说明,该方法可以明显改善插值放大效果.     

逆合成孔径雷达信号处理方法研究进展

在简要评述国内外现有的逆合成孔径雷达（ISAR）信号处理的运动补偿和成象方法之后，介绍了南京航空航天大学ISAR课题组近年来在ISAR信号处理方法研究中取得的主要进展，包括基于多散射点定位观点的雷达成象观测模型，基于最大似然原理的同时运动补偿和成象方法，基于最大似然原理的多目标成象方法和基于时频分析的多目标成象方法，以及超分辩成象方法，文末指出了在ISAR信号处理方面有待进一步研究的问题。     

红外隐身材料的研究进展

红外探测器的高度发展已使用于目标表面的热红外隐身材料成为飞行器隐身技术中的一个重要组成部分。但对这种材料的发展情况,以往的文献一向较少涉及。本文概括了这种材料的一般性能要求,较全面地评述了十余年来红外隐身材料研究中各主要方面的发展情况,并分析了一些重要材料品种的特点、性能水平、技术影响因素、存在的问题和发展趋势。     

基于幅度与梯度综合信息的SAR图像非线性扩散去噪方法

探讨SAR图像相干斑抑制的非线性扩散方程方法.以抑制SAR图像噪声,提高图像质量.通过分析SAR图像的幅度分布特性,建立基于SAR图像幅度信息的非线性扩散方程,使方程在幅值较小的背景区域具有较大的光滑作用以抑制噪声,而在幅值较大的目标区域光滑作用较小以保护目标特征.同时为避免噪声对图像中幅度分布的影响,在每一步迭代之前,采用基于梯度信息的非线性扩散方程对图像进行预处理,得到了一种基于图像幅度和梯度综合信息的非线性扩散去噪方法.计算结果表明,本文方法在整体上均具有较好的去噪效果,去噪后的图像较传统方法具有更高的等效视数和边缘保持指数,既能充分抑制背景区域的噪声,又能保护目标点,还很少出现虚假目标.