基于应用的可见光遥感图像质量评价方法研究

遥感应用需求的增加和应用水平的提高,对遥感图像质量提出越来越高的要求。为提高图像质量,一方面不断改进成像系统,另一方面也研究开发出各种图像处理方法,其中如何评价图像处理前后图像质量的变化是处理算法开发的重要环节。从应用的角度,通过对比评价图像处理前后的质量,初步研究提出了基于图像应用的主、客观评价方法,以找出算法处理的薄弱环节,为算法的优化提供支持。     

遥感数字图像配准技术综述

图像配准技术是近年来迅速发展的图像处理技术之一,也是解决图像融合、图像镶嵌和变化检测等问题的必要前提,并在遥感、军事、医学、计算机视觉等众多领域都有广泛的应用.本文首先简要介绍了图像配准的步骤和过程,接着具体分析了目前几种常用的配准方法,并归纳总结了其在遥感领域应用中的技术特点,最后讨论了图像配准在遥感领域中的发展趋势.     

基于粗糙集支持向量机的遥感影像分类算法研究

近年来,随着遥感技术的飞速发展,遥感影像的处理和分类已成为遥感应用研究中的一个热点,粗糙集（RS）理论和支持向量机（SVM）在信息处理和分类方面具有独特的优势,本文将粗糙集支持向量机应用于遥感影像分类,简要介绍了粗糙集理论的基本概念和支持向量机的基本原理,将粗糙集理论的属性约简作为前置系统,剔除冗余属性,把SVM分类器作为后置系统,对遥感影像进行训练和分类,实验结果表明该模型不仅提高了系统运行的速度,而且分类性能有了一定的提高,为遥感影像分类提供了一条有效途径。     

基于深度卷积网络的高分遥感图像语义分割

随着我国高分对地观测系统的不断发展,对高分影像智能化分析与处理的应用需求愈来愈多,基于深度学习语义分割的影像分类也受到高度关注。作为近景图像语义分割的热点模型,Deeplab网络在应用时取得了良好的效果。为了解决多尺度高分辨率遥感影像语义分割问题,本文首先利用空洞卷积扩大Atrous空间金字塔池化（ASPP）结构的感受野,然后对DeepLabv3进行改进并将其用于高分2号遥感影像的分类处理。我们以郴州地区的高分遥感影像为研究对方法进行了验证,首先对原始影像进行预处理,再对预处理图像进行数据增强与扩充,最后通过对不同参数条件下的分类结果进行对比,分析该模型的适应性和精确性。在我们的数据集中,本文方法的实验分类像素精度为88.2％,MIoU达到72.5％,得到了比Deeplab更好的分类效果。      

A new approach to vector median filtering based on space fillingcurves

The availability of a wide set of multidimensional information sources in different application fields (e.g., color cameras, multispectral remote sensing imagery devices, etc.) is the basis for the interest of image processing research on extensions of scalar nonlinear filtering approaches to multidimensional data filtering. A new approach to multidimensional median filtering is presented. The method is structured into two steps. Absolute sorting of the vectorial space based on Peano space filling curves is proposed as a preliminary step in order to map vectorial data onto an appropriate one-dimensional (1-D) space. Then, a scalar median filtering operation is applied. The main advantage of the proposed approach is the computational efficiency of the absolute sorting step, which makes the method globally faster than existing median filtering techniques. This is particularly important when dealing with a large amount of data (e.g., image sequences). Presented results also show that the filtering performances of the proposed approach are comparable with those of vector median filters presented in the literature.     

Incremental refinement of image salient-point detection

Low-level image analysis systems typically detect "points of interest", i.e., areas of natural images that contain corners or edges. Most of the robust and computationally efficient detectors proposed for this task use the autocorrelation matrix of the localized image derivatives. Although the performance of such detectors and their suitability for particular applications has been studied in relevant literature, their behavior under limited input source (image) precision or limited computational or energy resources is largely unknown. All existing frameworks assume that the input image is readily available for processing and that sufficient computational and energy resources exist for the completion of the result. Nevertheless, recent advances in incremental image sensors or compressed sensing, as well as the demand for low-complexity scene analysis in sensor networks now challenge these assumptions. In this paper, we investigate an approach to compute salient points of images incrementally, i.e., the salient point detector can operate with a coarsely quantized input image representation and successively refine the result (the derived salient points) as the image precision is successively refined by the sensor. This has the advantage that the image sensing and the salient point detection can be terminated at any input image precision (e.g., bound set by the sensory equipment or by computation, or by the salient point accuracy required by the application) and the obtained salient points under this precision are readily available. We focus on the popular detector proposed by Harris and Stephens and demonstrate how such an approach can operate when the image samples are refined in a bitwise manner, i.e., the image bitplanes are received one-by-one from the image sensor. We estimate the required energy for image sensing as well as the computation required for the salient point detection based on stochastic source modeling. The computation and energy required by the proposed incremental refinement approach is compared against the conventional salient-point detector realization that operates directly on each source precision and cannot refine the result. Our experiments demonstrate the feasibility of incremental approaches for salient point detection in various classes of natural images. In addition, a first comparison between the results obtained by the intermediate detectors is presented and a novel application for adaptive low-energy image sensing based on points of saliency is presented.     

CCD推扫遥感成像中的欠采样噪声处理

欠采样噪声产生分布于整个画面的小尺寸附加像,给目标识别等应用带来困难.本文推导并优化了CCD图像捕捉系统中消欠采样噪声算法,提出新的CCD推扫和采样数据处理方法,在CCD只能有推扫方向位移的遥感成像应用条件下,消除了图像中的欠采样噪声.扫描位移误差小于CCD间隔的1/4范围内,能消除或减小欠采样噪声.图像处理实验结果证明了欠采样噪声处理方法的正确性和有效性.     

Human-centered concepts for exploration and understanding of Earth observation images

The progress in information retrieval, computer vision, and image analysis makes it possible to establish very complete bases of algorithms and operators. A specialist in remote sensing or image processing now has the tools that allow him, at least in theory, to configure applications solving complex problems of image understanding. However, in reality, earth observation (EO) data analysis is still performed in a very laborious way at the end of repeated cycles of trial and error. To overcome this, we proposed a novel advanced remote sensing information processing system knowledge-driven information mining (KIM). KIM is based on human-centered concepts (HCCs), which implements new features and functions allowing improved feature extraction, search on a semantic level, the availability of collected knowledge, interactive knowledge discovery, and new visual user interfaces. We assess the HCC methodology for solving several difficult tasks in EO image interpretation, using a broad variety of sensor data, from meter-resolution synthetic aperture radar and optical images to hyperspectral data.     

地理信息系统及其在海洋科学中的应用

地理信息系统是处理地理信息的系统,简称GIS,包括空间定位数据、图形数据、遥感图像数据、属性数据等,用于采集、存储、管理、处理、检索、分析和表达地理空间数据的计算机系统,是分析海量地理数据的通用技术.具有地图处理、数据库和空间分析这三大功能,可以根据现有情况预测火情,也可以准确寻找鱼群,可以使短期内捕鱼量增长,但不能持续增加,很多渔民已经开始利用该项技术.本文主要分析了地理信息系统的发展趋势,对地理信息系统在海洋科学中的应用进行了简要的阐述.     

基于多特征融合的层次支持向量机遥感图像云检测

云检测是遥感图像处理和应用的前提,针对遥感图像云检测的准确率容易受到薄云及似云地物影响的挑战,提出一种结合遥感影像灰度、纹理和频率特征的层次支持向量机云检测算法.该方法首先采用简单线性迭代聚类算法将遥感图像分割为像素块,再采用一种层次支持向量机分类器对遥感图像以像素块为单位进行云检测.层次支持向量机的第一层将像素块初步...     

Shared workspaces for group collaboration: an experiment usingInternet and UNIX interprocess communications

The system described is intended to link institutions (such as universities or industrial research organizations) that have most of their computers connected to local area networks (LANs). The main objective of the research is to bring users of remote systems together to collaborate in reviewing and editing documents containing text, graphs and image objects. The term workspace is used to denote a collection of such objects belonging to some application, and the software tools needed to access these objects. The major components of the system and the user interface are presented. A prototype implemented in C under 4.3BSD UNIX is discussed. The system is then related to and contrasted with other work on group collaboration. The suitability and shortcomings of UNIX as an operating system for building group collaboration software tools are assessed     

DSM perspective: another point of view

Distributed shared memory computers (DSMs) have arrived (G. Bell, 1992; 1996) to challenge mainframes. DSMs scale to 128 processors with two to eight processor nodes. As shared memory multiprocessors (SMPs), DSMs provide a single system image and maintain a “shared everything” model. Large scale UNIX servers using the SMP architecture challenge mainframes in legacy use and applications. These have up to 64 processors and a more uniform memory access. In contrast, clusters both complement and compete with SMPs and DSMs, using a “shared nothing” model. Clusters built from commodity computers, switches, and operating system scale to almost arbitrary sizes at lower cost while trading off SMPs single system image. Clusters are required for high availability applications. Highest performance scientific computers use the cluster (or MPP) approach. High growth markets, e.g., Internet servers, online transmission processing (OLTP), and database systems can all use clusters. The mainframe future of DSM may be questionable because: small SMPs are not as cost effective unless built from commodity components; large SMPs can be built without the DSM approach; and clusters are a cost effective alternative for most applications to SMPs, including DSMs for a wide scaling range. Nevertheless, commercial DSMs are being introduced that compete with SMPs over a broad range     

静止轨道遥感卫星海面运动舰船快速检测方法

面向静止轨道光学遥感卫星,该文提出一种海上运动舰船目标快速检测方法。该方法首先利用多结构多尺度形态学滤波对海洋背景遥感图像进行背景抑制;然后采用自适应阈值分割和自组织聚类获得候选目标;再根据目标运动特征,利用静止轨道卫星凝视序列图像对候选目标进行多目标移动式邻域判决,剔除虚假目标;最后关联舰船目标以及融合卫星平台数据,可快速计算舰船状态等深层次动态信息。实验结果与分析表明,所提方法能有效检测海洋背景遥感图像中的多个运动舰船目标,准确获取各个舰船位置、航速、航向、运动轨迹等信息,具有算法简单,目标检测率高、虚警率低,稳定性好等优点。该方法为我国静止轨道光学遥感卫星在轨数据处理与应用提供了技术支撑。     

Automated Hyperspectral Cueing for Civilian Search and Rescue

Hyperspectral remote sensing provides information related to surface material characteristics that can be exploited to perform automated detection of targets of interest and has been applied to a variety of remote sensing applications. This paper explores the application to civilian search and rescue, using the Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) system developed for the Civil Air Patrol as a key example of how evolving hyperspectral technology can be employed to support these operations. ARCHER combines a visible/near-infrared hyperspectral imaging system, a high-resolution visible panchromatic imaging sensor, and an integrated geopositioning and inertial navigation unit with onboard real-time processing for data acquisition and correction, precision image georegistration, and target detection and cueing. Processing for detecting downed aircraft wreckage and other related objects employs real-time adaptive anomaly detection and matched filtering algorithms, and a non-real-time change detection mode to provide further false alarm reduction in some instances. This paper describes the system technology, with an emphasis on the current and evolving automated target detection methods, and summarizes the operational experience in the airborne employment against civilian search and rescue missions.      

图信号处理在高光谱图像处理领域的典型应用

高光谱图像(HSI)具有纳米级的光谱分辨能力且同时对地物目标的光谱维和空间维进行联合成像的优势,能够精细化感知场景目标的本征判别属性,在遥感探测、医疗诊断和国防安全等具有重要应用价值,是高精度遥感探测的科技制高点之一。不同于传统1维时间信号、2维图像信号,高光谱图像具有多阶、高维的信号属性。为解决传统信号处理方法在高光谱图像处理领域中的不足,图信号处理(GSP)理论与方法被逐渐引入高光谱图像处理与解译等任务中。该文以短综述的形式,介绍了图信号处理在高光谱图像处理领域的理论发展并列举了在高光谱特征提取、图像重构和解译分类3个主要方面的典型应用。最后,进一步探讨了该方向未来发展所面临的挑战和相应解决办法。     

双通道离轴遥感相机高稳定性光机结构设计

多光谱遥感相机提供的光谱图像信息具有极高的应用价值。为突破CCD成像器件谱段数量的限制、增加单台相机的谱段数量,提出了一种双通道的解决方法。从光学系统入手,对一种双通道离轴多光谱遥感相机进行了高稳定性光机结构设计。首先,通过使用四点球头支撑技术实现了对大口径主镜的高稳定性支撑,保证了在各个工况下反射镜面形精度满足使用要求。之后,对相机的焦面组件、主框架及隔振系统进行了设计及优化,保证了双通道离轴遥感相机在提供八个多光谱谱段的同时,具有良好的结构稳定性。最后,对整个相机进行有限元分析和力学环境试验,结果表明相机具有较高的稳定性,符合设计预期。     

大幅面遥感影像分发技术研究

在分析大幅面遥感影像分发应用需求的基础上,研究具有边缘提取能力的形态小波变换影像压缩技术和影像拆分等关键技术。将其应用到遥感影像分发系统,提出了影像分发服务和影像规范化服务的体系结构。介绍了系统组成,给出了影像产品规范化技术指标,重点描述了大幅面遥感影像规范化处理方法和流程。     

Automatic Spectral Rule-Based Preliminary Mapping of Calibrated Landsat TM and ETM+ Images

Based on purely spectral-domain prior knowledge taken from the remote sensing (RS) literature, an original spectral (fuzzy) rule-based per-pixel classifier is proposed. Requiring no training and supervision to run, the proposed spectral rule-based system is suitable for the preliminary classification (primal sketch, in the Marr sense) of Landsat-5 Thematic Mapper and Landsat-7 Enhanced Thematic Mapper Plus images calibrated into planetary reflectance (albedo) and at-satellite temperature. The classification system consists of a modular hierarchical top-down processing structure, which is adaptive to image statistics, computationally efficient, and easy to modify, augment, or scale to other sensors' spectral properties, like those of the Advanced Spaceborne Thermal Emission and Reflection Radiometer and of the Satellite Pour l'Observation de la Terre (SPOT-4 and -5). As output, the proposed system detects a set of meaningful and reliable fuzzy spectral layers (strata) consistent (in terms of one-to-one or many-to-one relationships) with land cover classes found in levels I and II of the U.S. Geological Survey classification scheme. Although kernel spectral categories (e.g., strong vegetation) are detected without requiring any reference sample, their symbolic meaning is intermediate between those (low) of clusters and segments and those (high) of land cover classes (e.g., forest). This means that the application domain of the kernel spectral strata is by no means alternative to RS data clustering, image segmentation, and land cover classification. Rather, prior knowledge-based kernel spectral categories are naturally suitable for driving stratified application-specific classification, clustering, or segmentation of RS imagery that could involve training and supervision. The efficacy and robustness of the proposed rule-based system are tested in two operational RS image classification problems.     

Combining high-performance computing and networking for advanced3-D cardiac imaging

The paper deals with the integration of a powerful parallel computer based image analysis and visualization system for cardiology into a hospital information system. Further services are remote access to the hospital Web server through an Internet network. The visualization system includes dynamic three dimensional representation of two types of medical images (e.g., magnetic resonance and nuclear medicine) as well as two images in the same modality (e.g., basal versus stress images). A series of software tools for quantitative image analysis developed for supporting diagnosis of cardiac disease are also available, including automated image segmentation and quantitative time evaluation of left ventricular volumes and related indices during cardiac cycle, myocardial mass, and myocardial perfusion indices. The system has been tested both at a specialized cardiologic center and for remote consultation in diagnosis of cardiac disease by using anatomical and perfusion magnetic resonance images     

基于成像模型的遥感数据分析与信息提取研究

针对遥感成像过程中普遍存在的退化现象,通过遥感成像模拟,揭示了不同退化程度对遥感数据质量的影响,反映了考虑成像退化因素对提高卫星遥感数据信息提取能力的作用.基于成像退化采用的支持向量机方法对遥感图像地物分类的实验研究表明,这种方法使遥感图像地物分类精度得到明显提高,特别是支持向量机方法与图像恢复技术的结合,效果更为明显.