临汾市近20年植被覆盖度遥感估算及动态变化分析

植被覆盖度是衡量植被生长状况的指标，对分析评价区域生态环境具有重要意义。以临汾市1998年、2007年和2018年Landsat遥感影像作为数据源，利用ENVI和ARCGIS软件，通过计算归一化植被指数（NDVI）值，利用像元二分模型，对临汾市近20年的植被覆盖度及其动态变化进行分析。分析结果显示:1998年、2007年和2018年临汾市的平均植被覆盖度分别为45.92%、58.76%和60.09%，处于递增的态势。在这20年间，极低覆盖度和低覆盖度的植被面积都有减少，而中等覆盖度、高覆盖度和极高覆盖度的植被面积增加。高覆盖度和低覆盖度的植被面积变化最大，高覆盖度的植被面积增加了3 063.14 km²，约占临汾市总面积的15.21%；低覆盖度的植被面积减少了3 192.38 km²，约占临汾市总面积的15.85%。说明临汾市的生态环境有所改善，这与该区水土保持项目的实施以及封禁治理有关。     

线性混合光谱模型在植被高光谱遥感分类中的应用研究

遥感图像中普遍存在着混合像元 ,这部分像元的分解一直是遥感应用研究的热点和难点 ,该文简要介绍混合像元的概念、研究现状和广泛用于混合像元分解的线性混合光谱模型及其解算方法 ,然后以OMISⅠ高光谱遥感数据为例 ,通过大量实验对该模型在植被高光谱遥感分类中的应用做了详细地探讨和分析。     

基于网格模型的混凝土细观结构数值模拟

基于改进的网格模型,模拟了全级配数值试件在轴向受压下的力学行为。讨论了W e ibu ll分布中的均质度、同一级配不同骨料分布对数值结果的影响。     

pH值对废水中氨氮监测结果的影响

简要地介绍了像素工厂,探讨了在像素工厂中对无人机遥感影像进行空三测量方法。实现了像素工厂无人机空三成果与传统数字摄影测量工作站的无缝衔接,并对采集的要素进行实地精度检测分析,形成了利用无人机遥感影像进行3D产品生产的作业体系。     

自适应窗口形状的中值滤波

中值滤波去除噪声的同时,难免出现含有线形图像的边缘轮廓信息跟随丢失的情况。为了达到滤除图像噪声最大化,有用信息损失最小化的目的,根据图像边缘特征选择或设计了适当大小和形状的窗口来进行中值滤波等操作。一方面,创新性地提出将Hough变换应用到车轮裂缝CT图像的滤波窗口形状的选择上,针对单一方向轮廓的图像,利用Hough变换检测出裂缝的方向,从而采用与裂缝形状相应的窗口对裂缝进行有针对性滤波,将该方法与传统方法进行了对比实验,并将60层滤波后切片图像堆栈得到了三维图像;另一方面,针对含有多个方向轮廓的图像,为了进一步改善滤波效果,提出根据像素梯度设计斜向滤波器,对多方向的线对进行滤波,数据显示经改进方法滤波后图像的峰值信噪比(PSNR)较传统的中值滤波提高了4~6,结构相似性(SSIM)提高了1%~2%左右,最后用683层荞麦切片CT图堆栈得到三维图像,对比滤波前后图像,可知该方法滤波效果良好。     

移动机器人导航中激光雷达测距性能研究

距离检测是移动机器人导航的一个关键问题.文章介绍了基于飞行时间法测距的二维激光雷达LMS291的工作原理,分析了影响LMS291测距性能的误差因素,通过统计分析对测距数据进行标定,研究了不同物体表面属性对测距精度的影响;通过混合像素测定方法确定LMS291的角度分辨率;通过对激光雷达测距性能的试验,建立测距误差模型.所得结论可以为复杂非结构化环境下移动机器人导航中障碍检测、环境建模及自定位提供支持.     

基于加权相关信号子空间的多频相位融合方法

针对多频干涉合成孔径雷达(InSAR)干涉信号不同频率分量的相位融合问题,提出基于加权相关信号子空间方法(CSSM)的多频相位融合方法。该融合方法采用联合像素模型构建信号模型;对 CSSM构造聚焦矩阵的思想进行改进,通过对各频率分量对应的协方差矩阵进行加权聚焦应对不同频率分量的信噪比差异;并采用联合子空间投影方法估计干涉相位。仿真数据和 SIR-C雷达实际数据验证表明,该方法能够有效改善多频 InSAR的干涉相位估计性能。     

An analysis of the transition proportion for binarization in handwritten historical documents

In this paper, we will present a mathematical analysis of the transition proportion for the normal threshold (NorT) based on the transition method. The transition proportion is a parameter of NorT which plays an important role in the theoretical development of NorT. We will study the mathematical forms of the quadratic equation from which NorT is computed. Through this analysis, we will describe how the transition proportion affects NorT. Then, we will prove that NorT is robust to inaccurate estimations of the transition proportion. Furthermore, our analysis extends to thresholding methods that rely on Bayes rule, and it also gives the mathematical bases for potential applications of the transition proportion as a feature to estimate stroke width and detect regions of interest. In the majority of our experiments, we used a database composed of small images that were extracted from DIBCO 2009 and H-DIBCO 2010 benchmarks. However, we also report evaluations using the original (H-)DIBCO?s benchmarks.     

Fast pixel-matching for video object segmentation

Video object segmentation, aiming to segment the foreground objects given the annotation of the first frame, has been attracting increasing attentions. Many state-of-the-art approaches have achieved great performance by relying on online model updating or mask-propagation techniques. However, most online models require high computational cost due to model fine-tuning during inference. Most mask-propagation based models are faster but with relatively low performance due to failure to adapt to object appearance variation. In this paper, we are aiming to design a new model to make a good balance between speed and performance. We propose a model, called NPMCA-net, which directly localizes foreground objects based on mask-propagation and non-local technique by matching pixels in reference and target frames. Since we bring in information of both first and previous frames, our network is robust to large object appearance variation, and can better adapt to occlusions. Extensive experiments show that our approach can achieve a new state-of-the-art performance with a fast speed at the same time (86.5% IoU on DAVIS-2016 and 72.2% IoU on DAVIS-2017, with speed of 0.11s per frame) under the same level comparison. Source code is available at https://github.com/siyueyu/NPMCA-net.