多光谱遥感图像压缩系统中的ROI编码方法

提出了一种基于EBCOT(率失真优化截取内嵌码块编码)算法的矩形ROI(感兴趣区域)编码的干涉多光谱卫星遥感图像压缩方法。该方法不需要对小波域的系数进行提升，而是在码流组织时通过对多光谱区域的误差跟踪提高恢复图像的质量。从而克服了传统方法因为增强系数与图像复杂度不匹配带来的ROI与BG的PSNR质量不协调的问题，该算法的解码器不需要知道该图像是否存在ROI，不需要反提升过程，完全正常解码即可，而且该方法保留了EBCOT的优良特性。实验表明，这种编码方式在干涉多光谱卫星图像压缩系统中可获得理想的效果。     

用于高温测量的红外热成像技术

用于高焓风洞实验中模型表面温度测量的CCD红外热成像系统 ,测温范围 1 0 0 0～ 350 0K。笔者介绍系统原理和标定过程 ,并给出了初步风洞实验结果。通过与红外高温计测量结果的比较分析 ,验证了该系统的可靠性和实用性。系统的研制成功为地面防热 /热结构实验中模型表面温度测量提供了先进的手段。     

双基地角时变下的ISAR等效旋转中心估计

双基地逆合成孔径雷达（ISAR）距离-多普勒算法成像时，容易引起越分辨单元徙动问题，影响成像质量，为了抑制越分辨单元徙动，需要估计目标的等效旋转中心。本文针对双基地角时变下的ISAR等效旋转中心估计问题，提出了一种等效旋转中心估计算法。该算法首先将运动补偿后的一维距离像序列分为两组并分别成像，得到两幅图像；其次，假定某个距离单元为等效旋转中心位置，对两幅图像进行畸变校正，使得两幅图像只存在一个视角差，按视角差旋转其中的一幅图像，并与另一幅图像作相关，得到相关系数；然后，假定下一个距离单元为等效旋转中心位置，重复上述步骤，直至遍历结束，相关系数最大值对应的假定位置就是估计的等效旋转中心。最后进行了仿真对比实验，表明本文算法能够有效估计双基地角时变下的ISAR等效旋转中心位置。     

基于多级并行处理的R-D方法的ISAR实时成像

论文对ISAR成像中R-D成像算法进行了介绍,在通用信号处理单元上合理地分配任务和映射算法,设计了多级并行处理的信号处理机结构,实现了R-D方法的ISAR实时成像处理。应用DMA方式实现数据的高速交互,利用二维DMA实现矩阵转置运算,并对程序进行优化设计,有效提高了算法执行效率。最后对处理结果和性能进行了分析,经过对PC机和实时信号处理机的成像结果对比,证明算法的实现是成功的。     

低信噪比下快速分裂Bregman迭代ISAR超分辨率成像

针对低信噪比条件下的逆合成孔径雷达ISAR(Inverse Synthetic Aperture Radar)超分辨率成像处理问题,提出了一种基于快速分裂Bregman迭代的ISAR超分辨率成像算法.首先,在正则化框架下,将方位分辨率的提高问题转化为一个正则化问题;其次,利用托普利兹矩阵的低位移秩特征和Gohberg-...     

二次多项式拟合外方位元素卫星三线阵C CD影像平差

文章针对一景大小的卫星三线阵CCD影像,采用二次多项式拟合外方位元素模型,与国外的定向片法模型进行平差算法对比.对一景大小的模拟数据进行了试验,结果表明基于二次多项式拟合外方位元素模型的平差方法有效的提高了影像的平面精度与高程精度,与定向片法模型相比,该算法简单,结果同样满足1∶5万摄影测量的要求.     

Earth-Based Visible and Near-IR Imaging of Mercury

New planned orbiter missions to Mercury have prompted renewed efforts to investigate the surface of Mercury via ground-based remote sensing. While the highest resolution instrumentation optical telescopes (e.g., HST) cannot be used at angular distances close to the Sun, advanced ground-based astronomical techniques and modern analytical and software can be used to obtain the resolved images of the poorly known or unknown part of Mercury. Our observations of the planet presented here were carried out in many observatories at morning and evening elongation of the planet. Stacking the acquired images of the hemisphere of Mercury, which was not observed by the Mariner 10 mission (1974–1975), is presented. Huge features found there change radically the existing hypothesis that the “continental” character of a surface may be attributed to the whole planet. We present the observational method, the data analysis approach, the resulting images and obtained properties of the Mercury’s surface.     

基于Hankel矩阵填充的稀疏孔径ISAR成像

在稀疏孔径(SA)逆合成孔径雷达(ISAR)成像中,传统压缩感知(CS)方法使用稀疏信号处理来处理数据缺失下的成像问题。这类方法存在模型不匹配这一固有问题,在一定程度上会限制成像质量。提出了一种利用Hankel矩阵填充(HMC)的基于结构化稀疏ISAR成像方法。该方法是一种典型的无网格方法,可以有效地提高稀疏孔径ISAR成像性能。首先,建立ISAR稀疏孔径成像信号模型,根据每个距离单元的回波构造Hankel矩阵;其次,通过证明所构造Hankel矩阵的低秩性质,作为方位稀疏成像的先验信息约束;最后,通过逐步迭代求解基于增广拉格朗日乘子(ALM)的矩阵填充(MC)来实现重构方位维成像。提出的基于低秩约束的方法,可以避免过完备基的假设,有效地克服了CS方法的离网格效应。基于实测数据的实验分析,进一步验证了所提算法的有效性。     

Development and testing of a statistical texture model for land cover classification of the Black Sea region with MODIS imagery

A statistical model is proposed for analysis of the texture of land cover types for global and regional land cover classification by using texture features extracted by multiresolution image analysis techniques. It consists of four novel indices representing second-order texture, which are calculated after wavelet decomposition of an image and after texture extraction by a new approach that makes use of a four-pixel texture unit. The model was applied to four satellite images of the Black Sea region, obtained by Terra/MODIS and Aqua/MODIS at different spatial resolution. In single texture classification experiments, we used 15 subimages (50 × 50 pixels) of the selected classes of land covers that are present in the satellite images studied. These subimages were subjected to one-level and two-level decompositions by using orthonormal spline and Gabor-like spline wavelets. The texture indices were calculated and used as feature vectors in the supervised classification system with neural networks. The testing of the model was based on the use of two kinds of widely accepted statistical texture quantities: five texture features determined by the co-occurrence matrix (angular second moment, contrast, correlation, inverse difference moment, entropy), and four statistical texture features determined after the wavelet transformation (mean, standard deviation, energy, entropy). The supervised neural network classification was performed and the discrimination ability of the proposed texture indices was found comparable with that for the sets of five GLCM texture features and four wavelet-based texture features. The results obtained from the neural network classifier showed that the proposed texture model yielded an accuracy of 92.86% on average after orthonormal wavelet decomposition and 100% after Gabor-like wavelet decomposition for texture classification of the examined land cover types on satellite images.