结构面粗糙度系数Barton直边法的简明公式

JRC是反映爬坡角力学效应的岩体结构面表面形态等效描述指标。本文在Barton直边法的研究基础上,利用直边图的几何性质,推导出结构面粗糙度系数Barton直边法的简明公式,并通过实例检验了JRC简明公式的合理性和实用性。     

三种遥感反演海岸线方法的实验对比分析

在分析海岸线提取算法基础上,以环渤海的Landsat7 ETM+影像为数据源,以基岩海岸线和淤泥质海岸线两种典型的海岸线为研究对象,采用Sobel边缘检测算法、阈值分割法和K最邻近分类算法进行海岸线提取实验。通过实验对比分析,归纳和总结了针对不同类型海岸线提取算法的适用性。     

基于残余插值的卷积神经网络去马赛克算法

在去马赛克问题中,为了精确插值倾斜边缘并提高结果图像的整体质量,提出一种基于残余插值的卷积神经网络去马赛克算法.针对Bayer格式的颜色滤波阵列,插值绿色平面时,对于红蓝通道信息不全的问题,采用同通道邻近像素值近似代替,综合考虑3个通道的梯度,运用倾斜方向的边缘检测算子,将倾斜边缘分为不同方向的边缘分别插值.在插值完成后,利用深度卷积神经网络,进一步训练插值结果.在标准的IMAX数据集上,与目前流行的算法相比,本文算法视觉上更接近原图,具有更高的峰值信噪比和更短的运行时间.     

一种改进的SAR影像边缘检测方法

由于SAR影像具有乘性相干斑噪声,某些对光学影像有较好检测性能的边缘检测算子,对于SAR影像并不适用,因此本文提出了一种将改进后的Ratio算子与Canny算子相组合的新方法。首先采用多种客观评价指标,得出经典方法中的Lee滤波能有效去除噪声,且最大限度保留了梯度信息,适用于边缘检测;然后对边缘检测具有恒虚警特性的Ratio算子进行改进,改进后的算子更利于影像归一化处理;最后利用改进后的Ratio算子与Canny算子组合成新方法。试验结果证明,组合后的新方法显著提高了边缘检测正确率和定位精度,改善了边缘连续性,具有一定的有效性和实用性。     

2013年甘肃岷县漳县6.6级地震前后重力场动态变化

利用青藏高原东北缘2011-2013年期间的流动重力观测资料,系统分析了区域重力场动态变化及其与2013年7月22 H岷县漳县6.6级地震发生的关系.结果表明:1)测区内重力场异常变化与主要断裂带在空间上关系密切,反映沿主要断裂带(段)在2011-2013年期间发生了引起地表重力变化效应的构造活动或变形.2)岷县漳县6.6级地震前,测区内先出现了较大空间范围的区域性重力异常,后在震源区附近产生了局部重力异常及重力变化高梯度带,其中,甘肃临夏与岷县一带重力差异变化达150×10 8ms-2以上;这些可能反映岷县漳县地震前,区域及震源区附近均产生与该地震孕育、发生有关的构造运动或应力增强作用.3)重力场1a尺度动态变化图像和差分动态演化图像均反映岷县漳县6.6级地震孕育过程的最后2a出现较显著的流动重力异常变化,地震发生在NE向重力变化高梯度带上、重力变化零值线附近和等值线的拐弯部位.4)基于流动重力异常变化在岷县漳县6.6级地震前做过一定程度的中期预测,尤其是地点判定.     

Shelf‐margin clinothem progradation,degradation and readjustment: Tanqua depocentre,Karoo Basin (South Africa)

Degradation of basin‐margin clinothems around the shelf‐edge rollover zone may lead to the generation of conduits through which gravity flows transport sediment downslope. Many studies from seismic‐reflection data sets show these features, but they lack small‐scale (centimetre to metre) sedimentary and stratigraphic observations on process interactions. Exhumed basin‐margin clinothems in the Tanqua depocentre (Karoo Basin) provide seismic‐reflection‐scale geometries and internal details of architecture with depositional dip and strike control. At the Geelhoek locality, clinothem parasequences comprise siltstone‐rich offshore deposits overlain by heterolithic prodelta facies and sandstone‐dominated deformed mouth bars. Three of these parasequences are truncated by a steep (6 to 22°), 100 m deep and 1·5 km wide asymmetrical composite erosion surface that delineates a shelf‐incised canyon. The fill, from base to top comprises: (i) thick‐bedded sandstone with intrabasinal clasts and multiple erosion surfaces; (ii) scour‐based interbedded sandstone and siltstone with tractional structures; and (iii) inverse‐graded to normal‐graded siltstone beds. An overlying 55 m thick coarsening‐upward parasequence fills the upper section of the canyon and extends across its interfluves. Younger parasequences display progressively shallower gradients during progradation and healing of the local accommodation. The incision surface resulted from initial oversteepening and high sediment supply triggering deformation and collapse at the shelf edge, enhanced by a relative sea‐level fall that did not result in subaerial exposure of the shelf edge. Previous work identified an underlying highly incised, sandstone‐rich shelf‐edge rollover zone across‐margin strike, suggesting that there was migration in the zone of shelf edge to upper‐slope incision over time. This study provides an unusual example of clinothem degradation and readjustment with three‐dimensional control in an exhumed basin‐margin succession. The work demonstrates that large‐scale erosion surfaces can develop and migrate due to a combination of factors at the shelf‐edge rollover zone and proposes additional criteria to predict clinothem incision and differential sediment bypass in consistently progradational systems.     

Clinoform architecture and along‐strike facies variability through an exhumed erosional to accretionary basin margin transition

Exhumed basin margin‐scale clinothems provide important archives for understanding process interactions and reconstructing the physiography of sedimentary basins. However, studies of coeval shelf through slope to basin‐floor deposits are rarely documented, mainly due to outcrop or subsurface dataset limitations. Unit G from the Laingsburg depocentre (Karoo Basin, South Africa) is a rare example of a complete basin margin scale clinothem (>60 km long, 200 m‐high), with >10 km of depositional strike control, which allows a quasi‐3D study of a preserved shelf‐slope‐basin floor transition over a ca. 1,200 km² area. Sand‐prone, wave‐influenced topset deposits close to the shelf‐edge rollover zone can be physically mapped down dip for ca. 10 km as they thicken and transition into heterolithic foreset/slope deposits. These deposits progressively fine and thin over tens of km farther down dip into sand‐starved bottomset/basin‐floor deposits. Only a few km along strike, the coeval foreset/slope deposits are bypass‐dominated with incisional features interpreted as minor slope conduits/gullies. The margin here is steeper, more channelized and records a stepped profile with evidence of sand‐filled intraslope topography, a preserved base‐of‐slope transition zone and sand‐rich bottomset/basin‐floor deposits. Unit G is interpreted as part of a composite depositional sequence that records a change in basin margin style from an underlying incised slope with large sand‐rich basin‐floor fans to an overlying accretion‐dominated shelf with limited sand supply to the slope and basin floor. The change in margin style is accompanied with decreased clinoform height/slope and increased shelf width. This is interpreted to reflect a transition in subsidence style from regional sag, driven by dynamic topography/inherited basement configuration, to early foreland basin flexural loading. Results of this study caution against reconstructing basin margin successions from partial datasets without accounting for temporal and spatial physiographic changes, with potential implications on predictive basin evolution models.     

遥感图像准无损压缩技术的研究

提出了一种基于图像恢复技术的遥感图像压缩技术,在提高遥感图像压缩比的同时,使压缩后的重建图像质量达到准无损的技术要求。对SRTF、TM图像的试验结果表明,该技术是可行的。     

一种新的超声波心动图像分割算法

针对超声心动图像噪声大,边界模糊,灰度分布不均匀等特点,提出了一种新的图像分割算法.首先对超声图像进行滤波和边缘锐化等预处理,然后再使用GVFSnake模型对预处理后的图像进行分割,从而提取出心室的边界.经试验证明,这种新的超声心动图像分割算法,比传统的超声图像分割算法在图像分割精度上有显著的提高.