磁扩散电弧运动图像实验研究

电弧等离子体与气体之间的相互作用机理研究一直在低温等离子领域受到关注。为了获得比较均匀的大面积直流电弧等离子流，设计了一种利用外磁场驱动电弧旋转的等离子发生器。利用高速摄影技术研究了大气压条件下氩电弧等离子体在弧室中的运动情况，得到了典型的螺旋型电弧照片，分析了外部磁场对电弧运动形状、电弧电压的影响和弧根附近的气流扰动情况，认为磁场分布的不均匀性是导致电弧形状多样性和不稳定性的主要原因，而阴极烧蚀引起了弧根区气流扰动的不对称性。     

序列图像中直线边缘快速提取和匹配

针时飞行器视觉导航等实时性较强的应用,给出了一种在航空序列图像中进行直线边缘快速提取和匹配的方案。在提取直线边缘时,运用了当前速度较快的邻接元素标记方法,从而提高了直线边缘提取速度。而在时直线边缘进行匹配时,给出了一种分三步走的方案,并提出了一种能够有效降低噪声影响的度量方式。首先选择3条直线边缘作为参考模型,在直线边缘的方向、位置以及物理特性的约束下构建候选匹配基,然后在基于矢量技术的基础上确定与参考模型基相对应的匹配模型,在此基础上再确定其他直线边缘之间的对应关系。试验结果表明,本文的直线边缘匹配方法比现有的方法速度提高了30倍以上,能够有效地满足一些实时性较强的应用。     

一种新颖的无人机侦察图像分区域压缩算法

针对无人机侦察图像及其在军事运用上的特点,分析并证明了基于小波变换的压缩技术在无人机侦察图像压缩方面是一种很好的解决方案,根据某型无人机侦察图像设计了一种基于小波变换的分区域压缩算法,取得了良好且满意的图像压缩效果和实时传输效果.最后,阐述了基于小波变换的侦察图像压缩的关键技术.     

一种红外成像引信中的飞机姿态识别方法

红外成像引信可以获得飞机的由完整到局部的一系列动态红外图像，飞机姿态识别对基于导引头信息利用的成像引信确定瞄准点具有非常重要的意义。文中分析了高速交会情况下飞机目标的运动特性，提出了一种飞机姿态识别方法，通过利用遗传算法确定像平面上飞机图像的旋转情况和机头位置，利用测距装置提供的距离信息、飞机图像的长度及红外探测器的系统参数确定飞机的俯仰情况，并利用弹目交会过程中机轴方位角和高低角的不变性重建局部成像跟踪情况下的空间机轴，最后实现了成像引信局部成像跟踪过程中飞机飞行姿态的识别。     

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。     

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.     

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.