基于小波变换的遥感影像压缩编码

基于小波变换的图像压缩方法能在高压缩比的前提下保持好的重建图像质量,它的多分辨率特性与人类视觉系统非常相近,小波变换的编码技术被广泛地应用于遥感影像的压缩中。介绍了小波理论的相关知识,着重对嵌入零树小波、等级树分割、小波数据的形态学表示算法等方法进行了详细的论述,并对图像编码技术的发展方向进行了展望。     

湖南汛期降水异常的时空分布特征研究

利用湖南19个测站23年(1959～2001年)4～9月的降水量资料，用EOF、REOF、小波分析对湖南汛期降水的特征场分布、分区特征、周期性和突变性等时空分布特征进行了诊断研究。研究结果表明：EOF分析得到的前三个典型场可以很好的反映湖南汛期降水空间分布的异常结构，即具有整体一致的空间结构，南北相反的空间结构，中部和周围地区相反变化的空间结构。旋转后的前6个空间模态可以较好地代表湖南汛期降水的6个异常敏感区：湘北、湘中、湘南、湘东南、湘西、湘东北。利用小波分析方法研究湖南汛期降水的周期性及其突变性发现，湖南汛期降水存在着明显的3年、7年和23年的特征时间尺度和周期性振荡；并且在今后相当长的一段时间内，湖南汛期的降水将逐年减少，并将转入干旱时期。     

基于小波分解的西太平洋副热带高压模糊推理预测

基于NCEP/NCAR再分析资料,讨论了西太平洋副高脊线与其前期位置的相互关系,并在此基础上用小波分解和自适应模糊推理方法,对副高脊线进行集成建模和预测.基于小波分解重构的副高脊线短期活动集成预测结果表明,该方法可有效降低预报难度,明显改进和提高了副高脊线短期活动的预报准确率.     

越南北部夏季降水特征及其与海温的联系

根据1958—1997年越南降水资料和NCEP／NCAR再分析资料，运用小波分析和相关分析等方法分析了越南北部降水特征及其与海温的联系。结果表明，越南北部降水主要集中在夏秋季；越南北部夏秋季降水具有明显的年际、年代际变化特征．并且与热带太平洋海温关系密切。在越南北部夏季多雨年，热带西太平洋海温异常偏高，中东太平洋海温异常偏低；而少雨年，则情况相反。     

新疆博格达山分段及深浅构造转换关系

研究表明 ,天山及邻区自中生代以来一直处于热衰减状态 ,博格达山新生代再造山具有“冷隆升”性 ,盆山边界断裂多限于上地壳内 ,而非直通中地壳低速体甚至上地幔的“深大断裂”。造山带内的韧性剪切带是在古生代形成的 ,而不是再造山期的断裂 ,它对造山带隆升及盆山耦合无贡献 ,博格达山的隆升为复式背斜构造所支持。博格达山与准东的关系为背斜北翼与盆地平缓基底构成的挠曲构造 ,而不是被深大断裂分隔的断块。博格达山具有独特鲜明的分段性 ,造山带的两个弧形构造与新生代再生前陆盆地构成独特的“斜方对称”分布样式。以板条观点为指导 ,从盆山单元的平面配置关系和深浅构造转换关系入手 ,探讨了博格达山板内造山阶段的几何学和运动学分段性的成因 ,构建了盆山耦合模式     

四川新康风化淋滤型海泡石的热相变研究

以四川新康风化淋滤型海泡石为研究对象，利用X射线衍射分析和红外光谱分析技术，对海泡石的热相变过程及特征进行了研究。结果发现，四川新康风化淋滤型海泡石的相变过程与沉积型、热液型海泡石相变过程明显不同，其相变过程可以划分为两个阶段：800℃以下保持海泡石相；800℃以上海泡石相转化为斜顽辉石相。     

小波模变换技术在探地雷达资料中的应用

通过研究探地雷达信号的小波变换的模特征点的变化规律和特征,揭示了探地雷达信号奇异点和其小波变换模极值的关系。通过这些关系的研究,对小波各级分解的模特征点进行变频域处理。最后对处理后的地质雷达信号,利用非线性最小二乘方法求解李氏指数,从而进行地质体边界的检测。无论从理论模型的论证还是实际资料的处理都取得了较好的结果。     

高速公路软基加固质量的瑞利波检测与小波分析技术

论述了用瑞利波检测高速公路软基加固的一些主要技术问题,应用新兴的小波分析技术,改善和提高检测的质量,并通过福宁高速公路的实际检测结果,说明了其思路和方法的正确性、实用性.     

Beds comprising debrite sandwiched within co-genetic turbidite: origin and widespread occurrence in distal depositional environments

Co‐genetic debrite–turbidite beds occur in a variety of modern and ancient turbidite systems. Their basic character is distinctive. An ungraded muddy sandstone interval is encased within mud‐poor graded sandstone, siltstone and mudstone. The muddy sandstone interval preserves evidence of en masse deposition and is thus termed a debrite. The mud‐poor sandstone, siltstone and mudstone show features indicating progressive layer‐by‐layer deposition and are thus called a turbidite. Palaeocurrent indicators, ubiquitous stratigraphic association and the position of hemipelagic intervals demonstrate that debrite and enclosing turbidite originate in the same event. Detailed field observations are presented for co‐genetic debrite–turbidite beds in three widespread sequences of variable age: the Miocene Marnoso Arenacea Formation in the Italian Apennines; the Silurian Aberystwyth Grits in Wales; and Quaternary deposits of the Agadir Basin, offshore Morocco. Deposition of these sequences occurred in similar unchannellized basin‐plain settings. Co‐genetic debrite–turbidite beds were deposited from longitudinally segregated flow events, comprising both debris flow and forerunning turbidity current. It is most likely that the debris flow was generated by relatively shallow (few tens of centimetres) erosion of mud‐rich sea‐floor sediment. Changes in the settling behaviour of sand grains from a muddy fluid as flows decelerated may also have contributed to debrite deposition. The association with distal settings results from the ubiquitous presence of muddy deposits in such locations, which may be eroded and disaggregated to form a cohesive debris flow. Debrite intervals may be extensive (> 26 × 10 km in the Marnoso Arenacea Formation) and are not restricted to basin margins. Such long debris flow run‐out on low‐gradient sea floor (< 0·1°) may simply be due to low yield strength (? 50 Pa) of the debris–water mixture. This study emphasizes that multiple flow types, and transformations between flow types, can occur within the distal parts of submarine flow events.     

Transformation of Residuals to Avoid Artifacts in Geostatistical Modelling with a Trend

Trend modelling is an important part of natural resource characterization. A common approach to account for a variable with a trend is to decompose it into a relatively smoothly varying trend and a more variable residual component. Then, the residuals are stochastically modelled independent of the trend. This decomposition can result in values outside the plausible range of variability, such as grades below zero or ratios that exceed 1.0. We transform the residuals conditional to the trend component to explicitly remove these complex features prior to geostatistical modelling. Back transformation of the modelled residual values allows the complex relations to be reproduced. A petroleum-related application shows the robustness of the proposed transformation. Furthermore, a mining application shows that when this conditional transformation is applied to the original variable, instead of the residual, simulated values are assured to be nonnegative.