排序方式: 共有27条查询结果,搜索用时 250 毫秒
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深部月壳和月幔物质结构是月球科学探测的关键问题之一。“嫦娥4号”初步将月球背面南极—艾肯(South Pole-Aitken,SPA)盆地内的冯·卡门(Von Kármán)撞击坑作为着陆点,具有重要的科学研究价值。结合月球重力、地形、布格重力、月壳厚度等地球物理数据,综合对冯·卡门撞击坑的月壳及其深部结构特征进行了分析。结果显示:冯·卡门撞击坑重复撞击到南部的冯·卡门M撞击坑上,后者的中央峰具有明显的布格正重力异常和线性的布格重力梯度特征,显示出高密度的幔部物质向上涌起;冯·卡门撞击坑极有可能穿透了该区域的整个月壳,并挖掘出了深部月幔的物质;该区域南部月壳厚度较薄小于5 km,北部平均月壳厚度在15~20 km,月壳平均密度为2 630 kg·m-3,比背面高地月壳密度高,且平均孔隙度为9%,低于月球的平均孔隙度12%。 相似文献
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Method of Passive Image Based Crater Autonomous Detection 总被引:1,自引:0,他引:1
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Detection of sub-kilometer craters in high resolution planetary images using shape and texture features 总被引:2,自引:0,他引:2
Lourenço Bandeira Wei Ding 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2012,49(1):64-74
Counting craters is a paramount tool of planetary analysis because it provides relative dating of planetary surfaces. Dating surfaces with high spatial resolution requires counting a very large number of small, sub-kilometer size craters. Exhaustive manual surveys of such craters over extensive regions are impractical, sparking interest in designing crater detection algorithms (CDAs). As a part of our effort to design a CDA, which is robust and practical for planetary research analysis, we propose a crater detection approach that utilizes both shape and texture features to identify efficiently sub-kilometer craters in high resolution panchromatic images. First, a mathematical morphology-based shape analysis is used to identify regions in an image that may contain craters; only those regions - crater candidates - are the subject of further processing. Second, image texture features in combination with the boosting ensemble supervised learning algorithm are used to accurately classify previously identified candidates into craters and non-craters. The design of the proposed CDA is described and its performance is evaluated using a high resolution image of Mars for which sub-kilometer craters have been manually identified. The overall detection rate of the proposed CDA is 81%, the branching factor is 0.14, and the overall quality factor is 72%. This performance is a significant improvement over the previous CDA based exclusively on the shape features. The combination of performance level and computational efficiency offered by this CDA makes it attractive for practical application. 相似文献
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月球背面南极—艾肯(South Pole-Aitken,SPA)盆地内的冯·卡门(Von Kármán)撞击坑是“嫦娥4号”初步选定的着陆区,该区域的地形地貌分析是任务设计的一个重要环节。根据LOLA (Lunar Orbiter Laser Altimeter)高程数据和LROC(Lunar Reconnaissance Orbiter Camera)影像数据,建立了马尔科夫随机场模型,从聚类的角度对该区域的地形地貌进行了表示和分析。具体而言,利用模型中的似然函数对呈近似正态分布的观测数据进行了建模,模型的标记随机场则刻画了不同地物形貌间的空间关系,并通过概率推断求解出最终的聚类结果。实验结果表明,从聚类角度进行数据表示,可以更好地展示出冯·卡门撞击坑内低对比度区域的地形地貌;而通过设置不同的聚类数目,还有助于分析冯·卡门撞击坑内整体的地形分布与局部的典型地貌。 相似文献
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行星表面陨石坑检测与匹配方法 总被引:2,自引:0,他引:2
针对深空探测器光学导航技术的需要,提出了行星表面陨石坑导航路标的提取与匹配方法。陨石坑是行星表面最显著的地形特征,在光照条件下,陨石坑具有清晰的几何轮廓。结合光照方向,通过陨石坑边缘的检测、边缘配对以及形状参数拟合等处理实现陨石坑的提取。对检测出的陨石坑,基于平面二次曲线的几何不变特性,采用投票策略实现与陨石坑数据库的匹配,并设计陨石坑误匹配及失配的校正策略,从而有效地确定陨石坑在目标天体表面的全局位置。最后通过嫦娥一号获得的目表图像验证了所提方法的有效性和可行性。 相似文献