基于偏微分的图像放大算法在视频监控中的应用

视频监控是安全防范系统的重要组成部分,它是一种防范能力较强的综合系统。视频监控以其直观、准确、及时和信息内容丰富而广泛应用于许多场合。针对视频监控中画面回放的特殊场合和获得较好的视觉效果的需求,相对于传统放大算法难以获得高分辨率的优质图像的缺点,基于偏微分的图像放大算法,能较好地保持图像的边缘特征和细节信息,从而获得清晰的放大图像。     

浅谈高清视频监控

自近几年“高清”的概念在视频监控行业火热以来,越多来越多的厂商开始推出“高清”化的产品。透过市场上种类繁多的“高清产品”,我们发现,有很多产品对“高清”的指标理解不一,表现效果也是千差万别。那么,视频监控行业“高清”的概念究竟是什么？什么才是真正的“高清”？本文中,我们浅作探讨。     

煤矿视频监控图像的改进非局部均值滤波算法

针对井下光线较差、粉尘大而导致视频监控图像清晰度不佳的问题,提出了一种改进非局部均值滤波算法。首先采用Log边缘检测算子对图像进行边缘提取,获得边缘和非边缘图像;然后分别从相似图像块获取方法以及权重值计算方法2个方面对非局部均值滤波算法进行改进,用于去除非边缘图像中的噪声点;最后将边缘图像与滤波后的非边缘图像进行融合。分别采用该算法与中值滤波算法、均值滤波算法、非局部均值滤波算法对现场采集的图像进行测试,结果表明该算法的图像处理效果明显优于其他算法。     

网络化高清视频监控系统解析

从全高清的角度分析了准东二矿网络化高清视频监控系统从前端信号采集、传输、解码、存储到显示、应用的全过程,重点分析了高清视频流对网络资源的占用以及控制方法。高清视频监控系统为直观调度指挥生产、辅助矿井综合自动化系统、保障生产安全奠定了基础。     

高清视频监控在校园安全防范中的应用

本文首先根据当前现状,分析了校园监控的意义,然后简单介绍了高清视频监控的发展现状,在此基础上,本文从需求分析、系统结构、系统功能等方面详细阐述了校园高清视频监控安防系统的技术方案,最后文章概括总结了系统的特点。     

图像监控系统浅议——公安视频图像监控联网平台

国内公安视频监控系统从最开始的单点监视到现在全城，全国范围的联网视频监控，监控系统已经从规模到功能上都发生了巨大的变化。本文结合目前的联网平台技术发展方向，深度剖析了视频图像监控联网所面临的问题。[编者按]     

基于监控视频图像的车辆测速

基于监控视频图像的车辆测速方法(视频测速)的工作原理，提出了一种视频测速的实现思路，指出了在间隔已知时间的视频帧图像中找到对应块是实现视频测速的关键和难点。对车灯的特征进行了分析，根据车灯区域的特征，提出了采用灰度差水平叠加投影的方法，构造可以代表其鼓形区域的函数，以其作为定位车灯带的判别函数，并根据车灯的特点进行候选块筛选的一种简单快速的车灯区域定位方法，可在平均13ms内准确定位到车灯区域，从而为这一高速条件下视频测速的关键难点提出了一种切实可行的解决办法。     

公安指挥中心中的集群多级视频图像监控系统

介绍了公安指挥中心中集群多级视频图像监空系统的基本结构和组网形式,并有该系统的主CPU软件进行了详细阐述。     

基于DM368的高清视频监控系统设计与实现

DM368作为高清数字摄像机智能图像分析处理器,集成了高性能元件,可以组建嵌入式视频监控系统,且接口丰富、使用便捷。因此,本文以DM368为基础阐述了高清视频监控系统的设计方法,并进一步分析了高清视频监控系统的实现路径。     

基于高分辨率SAR图像的道路自动提取

在传统算法的基础上,用多条件加权法进行道路边缘点的判断,充分利用道路的物理特性,将道路边缘点像素上下文特性作为判断的条件,以实现道路边缘线段的识别。桥接模式的思想是根据道路边缘线平行且宽度一定的特性,通过算法找出两条边缘线段之间的对应点,连接对应点以实现道路提取。经实验测试,该算法能消除地物间的影响和噪声干扰,有效地提高了道路提取的精度和速率。     

Procedures for correcting high resolution airborne video imagery

Airborne videography is a useful way of producing very high resolution remotely-sensed data. Before video data can be used for digital analysis, individual frames must be correcled for geometric distortion and brightness variation. The most obvious geometric distortion occurs because the odd and even fields in a video frame are collected sequentially and can be displaced relative to each other by aircraft roll and forward motion. We describe a procedure for correcting this distortion based on the cross-correla lion between individual fields at different spatial lags. Brightness variation across frames occurs because of dilTerences in viewing geometry, bi-directional reflectance variation and atmospheric scattering. We describe a method for removing much of this variation by calculating scattering angle across the image with an optional adjustment for sensor plane tilt. Relations between scattering angle and scene brightness statistics may then be calculated from sequences of images collected along a given transect. These relations can be used 10 normalise brightness. Tests of normalisation procedures based on mean, standard deviation, and median brightness show that the median gives the best results. This approach also produces better results than commonly-used band ratioing procedures.     

视频图像中运动目标的阴影消除法

针对在视频序列图像中运动目标的阴影造成运动目标的物理变形,影响运动目标的检测与跟踪;同时,由于目前常用的阴影检测算法,总是要先检测到阴影,再分割阴影,需两步才能达到消除阴影目的,难以达到实时检测要求。为此,提出了一种基于视频图像快速阴影消除方法。该方法通过分析阴影与背景的HSV彩色空间中的特性,利用阴影与运动目标在H,S,V三个分量中的不同特点,计算其相应的阈值,运用该阈值进行分割并消除阴影,能在视频序列图像中一次性检测到运动目标的同时就消除阴影。实验表明,在户外条件下,该算法是准确有效的。     

Road network extraction from high resolution satellite images

In this paper, an approach of roads network extraction from high resolution satellite images is presented. First, the approach extracts road surface from satellite image using one-class support vector machine(SVM). Second, the road topology is built from the road surface. The last output of the approach is a series of road segments which is represented by a sequence of points as well as the topological relations among them. The approach includes four steps. In the first step one-class support vector machine is used for classifying pixel of the satellite images to road class or non-road class. In the second step filling holes and connecting gaps for the SVM's classification result is applied through mathematical morphology close operation. In the third step the road segment is extracted by a series of operations which include skeletonization, thin, branch pruning and road segmentation. In the last step a geometrical adjustment process is applied through analyzing the road segment curvature. The experiment results demonstrate its robustness and viability on extracting road network from high resolution satellite images.     

辅以波谱分析的高分辨率影像面向对象分类研究

随着遥感影像空间分辨率的提高,地物的空间信息更加丰富,地物尺寸、 形状以及相邻地物的关系得到更好的反映,因此目前高分辨率影像分类方法更侧重于利用地 物的空间信息,分类过程中参与较多的人为主观因素,在地物类型未知的地区很难进行解译 工作。另外,分割过于细碎导致操作数据量太大也是高分辨率影像分类的难题之一。论文提 出了辅以波普分析的高分辨率影像面向对象分类方法,即在传统面向对象分类方法的基础上 结合影像波谱分析,先对影像光谱角制图粗分类、掩膜操作,再面向对象精分类,较好解决 了以往面向对象分类方法地物类型的不确定性和分割细碎等问题。试验以空间分辨率为0.5 米的八波段WorldView2 影像为研究数据提取西部那曲地区道路和河流,精度达到96.36%。     

Invariant models for ground control points in high resolution images

This paper addresses the problem of automatic identification of ground control points (GCPs) in high resolution satellite digital images. The method is based on characteristics of GCPs and their neighbourhood, invariant with respect to rotation and contrast change. The characterization algorithm, which leads to a feature space with a fixed number of dimensions a critical advantage of the method is based on the autocorrelation function of an azimuthal projection around the GCP. Such features are first extracted from a set of reference images and stored in a database, together with the GCP geographical co-ordinates, and used in Euclidean minimum distance classifier, looking for matches with pixels of the image being geo-referenced. Practical issues lead to the necessity to filter out potential wrong identifications, through a consistency filter based on geometrical patterns made of ambiguous GCPs. The performance of the method is studied, demonstrating its insensitivity with respect to rotation and variations of contrast, its discrimination power, and its sensitivity to determine the absolute position of a GCP to within a fraction of pixel.     

高分辨率合成孔径雷达图像的直线特征多尺度提取方法

针对传统的合成孔径雷达（SAR）多尺度边缘提取方法中直线提取连续性和完整性不好的特点,提出了一个由粗到精的多分辨率SAR图像直线特征多级提取框架,利用多尺度策略在降低SAR图像噪声影响的同时增强相邻共线点之间的连续性和完整性,并在不同的尺度图像中根据边缘特征的特点选择不同处理方法,来实现低分辨率条件下完整直线特征的粗略提取和高分辨率的精确定位。最后用高分辨率SAR图像跑道检测实验进行了验证,并将实验结果与相位编组法和Hough变换法进行了比较。     

Moment-based feature extraction from high spatial resolution hyperspectral images

In this article, we propose a method for extracting spatio-spectral features from high spatial resolution hyperspectral (HS) images. The method is based on extracting two-dimensional moments from neighbourhoods of pixels. Three different types of moments are considered: geometric, complex Zernike and Legendre. Moments of a given type are extracted from a few principal components (PC) of HS data, and are stacked on the original HS data to form a joint spatio-spectral feature space. These features are classified using a support vector machine (SVM) classifier. The influence of the moments orders and the size of the neighbourhood window on the quality of the extracted features are analysed. A few experiments are conducted on two widely used HS data sets, Pavia University and Salinas. The results demonstrate high capabilities of the proposed method in comparison with some state-of-the-art spatio-spectral HS classification methods.     

基于FPGA的四通道视频缩放引擎的研究及设计

设计了一种可实现4路视频信号缩放和帧率转换的电路架构.视频信号依次经过缩小模块、帧率转换模块以及放大模块,有效地减少了帧率转换对存储器带宽的需求.帧率变换模块采用输入和输出自适应调整的算法,同时在缩小模块采用加权均值算法,而放大模块则采用四点双三次插值算法.在满足视频放大质量要求的基础上,避免了采用过于复杂算法而消耗过...     

高分辨率SAR图像线状目标提取方法研究

本文针对高分辨率SAR影像进行城区河流、道路提取的算法研究,提出将纹理、面状和空间区域三种特征结合的方法。首先基于多尺度分析技术,结合面向对象的分割算法提取初始目标,之后使用灰度共生矩阵对目标及周边背景纹理进行差异对比分析去除误目标。与传统边缘检测方法相比,本文方法充分利用高分辨率SAR影像带来的纹理细节信息,并综合考虑目标的多种特征因素,增强了目标提取的可靠性,实用性强。