“百图齐放,殊图同归”——例谈高效地理复习中的“多图一用”

正纵观历年高考地理试题,几乎是"题题有图,无图不成题",图式的呈现往往比较新颖,因此读图能力的培养变得更加迫在眉睫。在此背景下,"多图一用"的教学方法受到众多一线教师的青睐。该方法是指复习中,在保持地理概念、规律等本质属性不变的前提下,从多角度、多侧面、多方位绘制图像,并通过图图转换,以多幅图像来呈现同一知识块,从而实现高三复习的高效化。     

人教版八年级下册新旧版本地理教材比较分析

正随着教育部《义务教育地理课程标准》(2011年版)的颁布,初中地理教材在原版基础上进行了一些改变,以适应新版课程标准以及社会发展的需要。新版教材与旧版教材相比很多方面均发生了改变。笔者对人教版八年级下册新旧版本地理教材从选择区域、活动栏目和图像系统等方面进行比较分析,以期为地理教师更好地使用新版教材提供参考。     

结合MapReduce和HBase的遥感图像并行分布式查询

提出了一种可扩展的遥感图像多维度并行查询模式,即利用MapReduce实现海量图像数据金字塔的并行构建,利用HBase实现图像的分布式检索,设计和实现了单张遥感图像金字塔的并行构建方法和图像索引系统。实验结果表明,随着Hadoop和HBase集群的增长,图像数据的导入和检索速度得到明显提升。     

海底三维声学图像实时处理系统设计

结合多核CPU硬件PC平台,设计了一种海底三维声学图像实时处理系统,主要包括声学前端信号处理子系统、数据传输控制子系统和PC客户端图像处理系统三个部分。声学前端信号处理子系统统根据接收到的多路声学换能器信号,通过两级FPGA信号处理,采集多通道水声信号,进行实时电子聚焦波束形成。为了解决海量声学数据快速传输问题,数据传输控制子系统未采用传统用户空间TCP/IP传输机制,而是直接通过嵌入式PowerPC处理器在Linux内核态采用DMA通道进行声学数据转发,减少系统调用和数据拷贝开销,有效提高网络传输效率。针对海量声学数据实时处理需求,PC客户端图像处理系统通过对复杂、耗时的单帧重建和数据拼接算法模块根据声学数据点的角度范围进行等分分割,对每个子范围声纳数据采用多线程并行处理,均衡多个CPU核之间负载,实现高性能三维声学图像实时处理。通过室内水池和湖试实验,结果表明该系统能够实时高效地进行三维声学图像采集、传输与处理。     

利用温度链对南海内波振幅的观测

内波的实测资料一般为走航或者浮标布站观测得到的一个关于时间和空间的大面资料,将此资料进行滤波后,进行简单的数值处理,即可得到内波的振幅。但是这种资料较少,布控站位难度较大,成本也较高,是一种不易获取的资料。本文利用的温度链资料是一种获取简单,成本也较低的实测资料。利用温度链资料基于内波带动水质点上下波动的物理过程,进行内波振幅的计算,将会有较大的适用性。     

Characterizing landscape spatial heterogeneity in multisensor images with variogram models

Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l＇observation de la Terre （SPOT）, Ad- vanced Spacebome Thermal Emission and Reflection Radiometer （ASTER） and Landsat Thematic Mapper （TM） images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands.     

基于参数切换混沌有序索引的图像行列置乱加密算法

为了提高加密算法的性能,设计一种基于改进型参数切换混沌的图像加密算法。首先根据符号逻辑映射序列自适应选择正弦、余弦或帐篷映射生成参数切换混沌随机序列。选取与行数、列数等长的混沌序列排序生成混沌有序索引值作为行列置乱索引,依次对图像按行、列进行置乱,将剩余混沌序列扩展后与置乱的图像像素按比特进行异或加密得到加密图像,提高密钥空间。实验结果表明,该算法的密钥空间较大,能够较好地抵抗攻击。     

基于遗传小波神经网络的海底声学底质识别分类

分割海底声纳探测图像,提取单元特征向量进行主成份分析,选取均值、标准差、对比度、相关系数、能量及同质性作为训练特征向量,构建小波神经网络。利用遗传算法优化小波神经网络的初始权值及小波参数,对砂、礁石、泥3种底质类型分别进行训练,并得到3种底质的测试精度都在90%以上,优于单独利用小波神经网络进行训练时的测试精度,克服了小波神经网络训练时易陷入局部极小的固有缺陷,表明基于遗传算法的小波神经网络可有效用于海底底质声纳图像的识别和分类。     

海岛礁光学和雷达影像基于改进非子采样小波变换的自动配准

Homologous feature point extraction is a key problem in the optical and synthetic aperture radar （SAR） image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform （TSO-NSWT） for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 （multi-spectral） and YG-1 （SAR） images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error （RMSE） patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition.     

基于平面基准深度图像建模的研究

散乱数据的TIN模型构建,存在数据量大、构网复杂、存储不便、内存消耗大等缺点。本文提出一种快速判断点在不规则多边形区域内的方法和快速提取点云边界的方法,继而提出一种基于平面基准的深度图像建模方法。该方法能够实现有效的快速构网、减少数据存储量、几何纹理清晰、纹理贴图方便、可进行多分辨率LOD(level of detail)表达等优点。