Glacier mapping based on rough set theory in the Manas River watershed

Precise glacier information is important for assessing climate change in remote mountain areas. To obtain more accurate glacier mapping, rough set theory, which can deal with vague and uncertainty information, was introduced to obtain optimal knowledge rules for glacier mapping. Optical images, thermal infrared band data, texture information and morphometric parameters were combined to build a decision table used in our proposed rough set theory method. After discretizing the real value attributes, decision rules were calculated through the decision rule generation algorithm for glacier mapping. A decision classifier based on the generated rules classified the multispectral image into glacier and non-glacier areas. The result of maximum likelihood classification (MLC) was used to compare with the result of the classification based on the rough set theory. Confusion matrix and visual interpretation were used to evaluate the overall accuracy of the results of the two methods. The accuracies of the rough set method and maximum likelihood classification were compared, yielding overall accuracies of 94.15% and 93.88%, respectively. It showed the area difference based on rough set was smaller by comparing the glacier areas of the rough set method and MLC with visual interpreter, respectively. The high accuracy for glacier mapping and the small area difference for glacier based on rough set theory demonstrated that this method was effective and promising for glacier mapping.     

面向GPU快速处理的地面材质数据压缩方法 陆巍巍 1,徐涛2,徐珂文 1

为解决雷达图像仿真中海量地面材质数据的存储和加载问题,采用基于自适应最大行程长度编码和修正 偶对的压缩算法进行材质数据的压缩,从而有效地减少了数据的存储量,消除数据传输的瓶颈,提高了数据传输的 吞吐能力。压缩算法面向 GPU快速处理,得到压缩数据适用于 GPU进行快速解压。     

基于方向可控金字塔的图像融合算法

为克服传统正交小波变换在进行图像融合时存在的不足,提出了一种基于方向可控金字塔的图像融合算法。首先对待融合图像进行方向可控金字塔分解,对分解后的低频分量采用平均和选择相结合的方法进行融合,对各方向的高频分量则使用像素绝对值选大的规则进行融合,最后对融合后的低频分量和高频分量进行方向可控金字塔重构得到融合图像。仿真试验表明算法能够得到质量较高的融合图像,同时,熵、平均梯度和空间频率等客观评价指标也较平均法和基于小波变换的图像融合算法有所提高,是一种有效的图像融合算法。     

Quality assessment by region in spot images fused by means dual-tree complex wavelet transform

This work is motivated in providing and evaluating a fusion algorithm of remotely sensed images, i.e. the fusion of a high spatial resolution panchromatic image with a multi-spectral image (also known as pansharpening) using the dual-tree complex wavelet transform (DT-CWT), an effective approach for conducting an analytic and oversampled wavelet transform to reduce aliasing, and in turn reduce shift dependence of the wavelet transform. The proposed scheme includes the definition of a model to establish how information will be extracted from the PAN band and how that information will be injected into the MS bands with low spatial resolution. The approach was applied to Spot 5 images where there are bands falling outside PAN’s spectrum. We propose an optional step in the quality evaluation protocol, which is to study the quality of the merger by regions, where each region represents a specific feature of the image. The results show that DT-CWT based approach offers good spatial quality while retaining the spectral information of original images, case SPOT 5. The additional step facilitates the identification of the most affected regions by the fusion process.     

随机-有界混合不确定性下结构可靠性优化设计

在结构可靠性分析和设计中,往往无法将所有不确定性参数均作为概率随机变量,存在部分不确定性分布特征不明确而仅知其扰动界限的情况.基于概率模型与多椭球模型的混合不确定性描述,以标准U空间中扩展定义的混合可靠性指标为约束条件,建立了随机不确定性和有界不确定性并存情况下的结构可靠性优化数学模型.利用功能测度方法对原优化模型进行...     

基于图像的发动机滑油滤磨屑定量分析技术

定量分析滑油滤磨屑是提高航空发动机内部磨损故障诊断成功率的有效技术途径.为满足某型航空发动机使用维护中滑油滤磨屑快速定量分析和磨损状态诊断的实际需求,设计制造了油滤磨屑自动清洗收集装置,采用电荷耦合器件(CCD)获取油滤磨屑数字图像,运用二维最大熵遗传算法对磨屑图像进行阈值分割后提取磨屑目标的特征量,将磨屑特征量与反映...     

不同结构等离子体激励器的流场特性实验研究

采用粒子成像测速(PIV)技术,在静止空气中测量了H型、O型和L型3种结构的介质阻挡等离子体激励器的诱导速度场,分析了流场结构,并研究了激励器设计参数对诱导速度的影响.研究结果表明,3种结构的激励器都产生了离开激励器表面向上的射流.其中O型和L型结构的激励器受电极电压的影响比较明显,随着电极电压的增加,射流速度的最大值...     

基于Rician分布的SAR图像MRG目标提取算法

针对SAR图像特有的乘性噪声和非恒虚警统计特性很难正确提取目标的问题,本文提出了MRG算法对SAR目标进行检测。首先用MRF-ICM算法对SAR图像进行后向散射系数的复原,再在复原后的幅度上叠加相位信息后引入Rician分布寻找自适应的最佳局域Gabor滤波器参数对SAR图像进行目标提取。和以往的算法相比,MRG算法充分利用了SAR图像幅度和相位中所携带的信息,能更准确地提取目标。实验表明:该方法能取得很好的目标检测效果,后期提取出的目标更符合实际目标形态,具有较强的通用性。     

改进U-Net网络及在遥感影像道路提取中的应用

高分辨率遥感图像分割在军事、民用等领域具有良好的应用前景,但由于复杂的背景条件以及干扰物的遮挡,导致现有算法无法较好地从遥感影像中提取道路细节信息。研究基于改进U Net网络模型,提出了MDAU-Net（multi dimension attention U-Net）网络结构模型,通过对U-Net网络结构加深至七层结构来提升精细分割道路的能力;并提出了一种多维注意力模块MD-MECA（multi dimension modified efficient channel attention）,将其添加至编码部分的特征传递步骤中,以达到对编码部分的特征传递进行优化的目的;其中利用DropBlock与Batch Normalization解决网络训练过程中出现的过拟合。试验结果表明:改进后算法可以有效提升道路的提取效果,在测试集上的准确率达到了97.04%。     

基于深度学习的SAR图像质量提升方法研究

提升合成孔径雷达(SAR)图像质量以增强其可判读性,一直是SAR图像处理中的关键问题。近年来,深度学习在光学图像处理中取得显著的成功,并逐步应用到SAR图像质量提升领域。对深度学习在SAR图像质量提升中的关键应用进行综述,对深度学习在SAR图像质量提升中采用的典型网络进行了介绍,并从SAR图像旁瓣抑制、超分辨(SR)处理和图像融合3个方面对深度学习的应用进行阐述。最后,分析与探讨了基于深度学习的SAR图像质量提升中的关键问题及进一步研究方向。