检索结果-内蒙古大学图书馆

SKATE: A Web-Based Seismogram Digitization Tool

SEISMOLOGICAL RESEARCH LETTERS 2018年第5期89卷 1886-1893页

作者： Bartlett, Andrew H. Lichtner, Benjamin A. Nita, Marius Yashar, Benamy Bartlett, Lowell E. Retriever Technol 1600 Lena StSTE D1 Santa Fe NM 87505 USA

Vast stores of paper- and film-based seismograms require novel solutions to extract their unique seismological data. We created a prototype software tool called SKATE (Software Kit for Automatic Trace Extraction) that is designed for high-speed, low-cost digitization of these archives. SKATE is a web-based program that requires a user only to navigate to a website (see Data and Resources) to begin digitizing seismogram images. The software is free, is server based, requires no software downloads, is open source, and has digitized up to the point of editing more than 30,000 World-Wide Standard Seismographic Network (WWSSN) images. It is based on a set of image-processing algorithms that identify real seismogram features while rejecting spurious noise and which attempts to assign these features to their proper place in a time series. Users can edit the results and download the data for further processing. The code is publicly available and is readily modifiable by qualified researchers.

关键词： computer software Downloading Software prototyping SKATE open source computer programs image processing algorithm Servers spurious noise digitization

来源：评论

学校读者我要写书评

暂无评论

An Unmanned Aerial Vehicle-Based Imaging System for 3D Measurement of Unpaved Road Surface Distresses

引用

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING 2012年第2期27卷 118-129页

作者： Zhang, Chunsun Elaksher, Ahmed Univ Melbourne Dept Infrastruct Engn Parkville Vic 3052 Australia St Cloud State Univ Land Surveying & Mapping Sci Program St Cloud MN 56301 USA

Road condition data are important in transportation management systems. Over the last decades, significant progress has been made and new approaches have been proposed for efficient collection of pavement condition data. However, the assessment of unpaved road conditions has been rarely addressed in transportation research. Unpaved roads constitute approximately 40% of the U.S. road network, and are the lifeline in rural areas. Thus, it is important for timely identification and rectification of deformation on such roads. This article introduces an innovative Unmanned Aerial Vehicle (UAV)-based digital imaging system focusing on efficient collection of surface condition data over rural roads. In contrast to other approaches, aerial assessment is proposed by exploring aerial imagery acquired from an unpiloted platform to derive a three-dimensional (3D) surface model over a road distress area for distress measurement. The system consists of a low-cost model helicopter equipped with a digital camera, a Global Positioning System (GPS) receiver and an Inertial Navigation System (INS), and a geomagnetic sensor. A set of image processing algorithms has been developed for precise orientation of the acquired images, and generation of 3D road surface models and orthoimages, which allows for accurate measurement of the size and the dimension of the road surface distresses. The developed system has been tested over several test sites with roads of various surface distresses. The experiments show that the system is capable for providing 3D information of surface distresses for road condition assessment. Experiment results demonstrate that the system is very promising and provides high accuracy and reliable results. Evaluation of the system using 2D and 3D models with known dimensions shows that subcentimeter measurement accuracy is readily achieved. The comparison of the derived 3D information with the onsite manual measurements of the road distresses reveals differences of 0.50

关键词： Road vehicle Three Dimensions rectification hay road distilling Pavement condition Unpaved roads PAVEMENTS dimensions image processing algorithm precise measurement

来源：评论

学校读者我要写书评

暂无评论

Economical thermal-RGB imaging system for monitoring agricultural crops

引用

COMPUTERS AND ELECTRONICS IN AGRICULTURE 2018年 147卷 34-43页

作者： Osroosh, Yasin Khot, Lav R. Peters, R. Troy Washington State Univ IAREC Ctr Precis & Automated Agr Syst Dept Biol Syst Engn Prosser WA 99350 USA

In this study, a low-cost thermal-RGB imager was developed for use in agricultural crop monitoring applications. It is weatherproof, and has a geo-referencing capability along with a power management panel that allows unattended field deployment of the systems for crop monitoring over extended period of time. The imager is made up of single-board Linux-based computer integrated with RGB and thermal imaging modules. The imager can be configured as FTP server to allow data transfer to/from a client computer. Developed was also the custom image-processing algorithm which overlays, aligns thermal and RGB images, and mask for the thermal image to remove the soil background and shaded leaves. The algorithm outputs are the average temperature of sunlit leaves and canopy coverage. Prior to field validation, the performance of ten thermal modules and four fully assembled RGB-thermal imagers were assessed under laboratory conditions. In the spring of 2017, two imagers were mounted on a center pivot retrofitted with Medium Elevation Spray Application (MESA) and Low Elevation Spray Application (LESA) systems in a mint field near Toppenish, WA. The thermal modules showed an accuracy of +/- 2.4 degrees C on average over a range of 0-50 degrees C of a blackbody target. Although accurate for larger canopies, the imperfect alignment of RGB and thermal images introduced significant errors in the calculations of sunlit leaves surface temperature in images with small canopy coverage. Further investigations revealed that the first peak of thermal image relative frequency histogram could be a more accurate representative of sunlit leaf surface temperature. Overall, the amended image-processing algorithm was able to successfully extract canopy surface temperature and percent canopy cover from a wide range of images captured during the crop growing season. The current design of imager allows for creating a network of imaging units in the field to obtain real-time surface temperature data f

关键词： Irrigated crops Center pivot Thermal-RGB imaging image processing algorithm Crop water status

来源：评论

学校读者我要写书评

暂无评论

A UNIVERSAL NONLINEAR COMPONENT AND ITS APPLICATION TO WSI

引用

IEEE TRANSACTIONS ON COMPONENTS HYBRIDS AND MANUFACTURING TECHNOLOGY 1993年第7期16卷 656-664页

作者： JAIN, VK WADEKAR, SA LIN, L UNIV S FLORIDA ARCHITECTURES APPLICAT & DESIGN GRPTAMPAFL 33620

This paper presents a high-speed multifunction chip for performing one of four nonlinear operations: 1) square root, 2) reciprocal, 3) sine/cosine, and 4) arctangent. Each of these functions is evaluated with one ROM access, two additions, and one major and one minor multiplication, yielding a new result every two clock cycles. Its performance signifies an estimated three-to-four-fold increase in speed (for comparable technologies and minimum feature size) over existing approaches. Furthermore, since all four functions are performed on the same cell, a silicon-area advantage of approximately three is realized when the application demands multiple functions. In wafer scale integration (WSI) of signal and image processing algorithms, several such functions are usually needed, while defect tolerance dictates the use of just one or two types of cells. Thus the new component is ideally suited for monolithic WSI. However, it can also be used as a co-processor/accelerator for commercial DSP chips in hybrid WSI implementation of signal processing algorithms. The underlying principle, which has made the combined goals of high-speed and multifunctionality possible, is second-order interpolation of very small ROM tables. Two versions am presented: a 24-b chip, and a 16-b chip, both fabricated in 2.0-mum CMOS technology. As an application example, a rapid prototyping wafer scale architecture is described.

关键词： nonlinear device feature size Wafer level packaging cell type image processing algorithm

来源：评论

学校读者我要写书评

暂无评论

Linear algorithms in Sublinear Time-a Tutorial on Statistical Estimation

引用

IEEE COMPUTER GRAPHICS AND APPLICATIONS 2011年第2期31卷 58-66页

作者： Ullrich, Torsten Fellner, Dieter W. Fraunhofer Austria Res Vienna Austria

This tutorial presents probability theory techniques for boosting linear algorithms. The approach is based on statistics and uses educated guesses instead of comprehensive calculations. Because estimates can be calcul... 详细信息

关键词： computations on discrete structures computer graphics geometrical problems and computations graphics and multimedia statistical computing COMPUTER GRAPHICS sublinear algorithms image processing algorithm Statistical Computing

来源：评论

学校读者我要写书评

暂无评论

Fast Fourier method for the accurate rotation of sampled images

引用

OPTICS COMMUNICATIONS 1997年第1-3期139卷 99-106页

作者： Larkin, KG Oldfield, MA Klemm, H UNIV SYDNEY SCH PHYSDEPT PHYS OPTSYDNEYNSW 2006AUSTRALIA UNIV SYDNEY AUSTRALIAN KEY CTR MICROSCOPY & MICROANALSYDNEYNSW 2006AUSTRALIA

At present the best methods for rotation of discrete sampled images use a combination of (fast) Fourier interpolation followed by cubic interpolation onto a rotated grid. A method is presented which uses only Fourier interpolation. The new method has a similar computational complexity to the old, and is exactly reversible. The method uses the well-known decomposition of rotation into three pure shears. Each shear is performed using a 2D extension of the 1D Fourier shift theorem. This allows the fast Fourier transform (FFT) to be used, With appropriate data padding (such as zero padding) in both the real and Fourier domains, the procedure gives near perfect results and minimal loss of information in multiple rotation tests.

关键词： Fourier interpolation digital image rotation lossless image transformation image warping image processing algorithm

来源：评论

学校读者我要写书评

暂无评论

Effect of spatial resolution on information content characterization in remote sensing imagery based on classification accuracy

引用

INTERNATIONAL JOURNAL OF REMOTE SENSING 2002年第3期23卷 537-553页

作者： Narayanan, RM Desetty, MK Univ Nebraska Dept Elect Engn Lincoln NE 68588 USA Univ Nebraska Ctr Electroopt Lincoln NE 68588 USA Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68588 USA

The information content of remote sensing imagery depends upon various factors such as spatial and radiometric resolutions, spatial scale of the features to be imaged, radiometric contrast between different target types, and also the final application for which the imagery has been acquired. Various textural measures are used to characterize the image information content, based upon which different image processing algorithms are employed to enhance this quantity. Previous work in this area has resulted in three different approaches for quantifying image information content, primarily based on interpretability, mutual information, and entropy. These approaches, although well refined, are difficult to apply to all types of remote sensing imagery. Our approach to quantifying image information content is based upon classification accuracy. We propose an exponential model for information content based upon target-background contrast, and target size relative to pixel size. The model is seen to be applicable for relating information content to spatial resolution for real Landsat Thematic Mapper ( TM) as well as Shuttle Imaging Radar-C ( SIR-C) images. An interesting conclusion that emerges from this model is that although the TM image has higher information content than the SIR-C image at smaller pixel sizes, the opposite is true at larger pixel sizes. The transition occurs at a pixel size of about 720 m. This tells us that for applications that require high resolution (or smaller pixel sizes), the TM sensor is more useful for terrain classification, while for applications involving lower resolutions (or larger pixel sizes), the SIR-C sensor has an advantage. Thus, the model is useful in comparing different sensor types for different applications.

关键词： image information remote sensing Shuttle Imaging Radar pixel terrain classification Spatial resolution image processing algorithm thulium

来源：评论

学校读者我要写书评

暂无评论

Visible defects detection based on UAV-based inspection in large-scale photovoltaic systems

引用

IET RENEWABLE POWER GENERATION 2017年第10期11卷 1234-1244页

作者： Li, Xiaoxia Yang, Qiang Chen, Zhebo Luo, Xuejing Yan, Wenjun Zhejiang Univ Coll Elect Engn Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Taizhou Inst Taizhou Zhejiang Peoples R China

The asset assessment and condition monitoring of large-scale photovoltaic (PV) systems spanning over a large geographical area has imposed urgent challenges and demands for novel and efficient inspection paradigm. In this study, an automatic UAV-based inspection system is presented and implemented for asset assessment and defect detection for large-scale PV systems. Two typical visible defects of PV modules, snail trails and dust shading, are characterised and the defect detection through image processing algorithms based on first order derivative of Gaussian function and feature matching is carried out for the aerial PV module images captured by visible light cameras. The functionality of the developed unmanned aerial vehicle (UAV)-based inspection system can be easily extended with more advanced fault detection algorithms and different forms of sensing devices (e.g. infrared thermal camera) for specialised inspection tasks. Such UAV-based imaging can carry out a variety of inspection and condition monitoring tasks in PV systems spanning over a large geographical area in an autonomous or supervised fashion with significantly promoted efficiency in comparison with conventional methods.

关键词： photovoltaic power systems inspection condition monitoring Gaussian processes image matching cameras image sensors autonomous aerial vehicles fault diagnosis power generation faults power engineering computing visible defect detection large-scale photovoltaic system asset assessment condition monitoring automatic UAV-based inspection system large scale PV system snail trail dust shading image processing algorithm Gaussian function feature matching aerial PV module visible light camera unmanned aerial vehicle advanced fault detection algorithm infrared thermal camera

来源：评论

学校读者我要写书评

暂无评论

Stochastic algorithm for approximating soft morphological operators

引用

OPTICAL ENGINEERING 2001年第12期40卷 2746-2752页

作者： Zmuda, MA Miami Univ Dept Comp Sci & Syst Anal Oxford OH 45056 USA

A technique that approximates the output of the soft morphological operators is described. The soft operators can be viewed as a voting process across neighborhoods defined by the structuring element. Instead of processing all votes across a neighborhood, this approximation technique randomly samples elements in the neighborhood and uses these values as inputs to a two-state finite state machine, where the state of the machine corresponds to the output at a given pixel. When properly designed, the machines sample a small fraction of the neighborhood, obtain output that is 91 to 100% accurate at each pixel, and is one to two orders of magnitude faster than conventional algorithms. Experiments on binary textures and digits confirm the theoretical results. (C) 2001 Society of Photo-Optical Instrumentation Engineers.

关键词： mathematical morphology image processing algorithm

来源：评论

学校读者我要写书评

暂无评论

A Matrix-Based Two-Dimensional Regularization algorithm for Signal-to-Noise Ratio Enhancement of Multidimensional Spectral Data

引用

APPLIED SPECTROSCOPY 2010年第11期64卷 1209-1219页

作者： Foist, Rod B. Schulze, H. Georg Jirasek, Andrew Ivanov, Andre Turner, Robin F. B. Univ British Columbia Michael Smith Labs Vancouver BC V6T 1Z4 Canada Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada Univ Victoria Dept Phys & Astron Victoria BC V8W 3P6 Canada Univ British Columbia Dept Chem Vancouver BC V6T 1Z1 Canada

We present a new spectral image processing algorithm, the "matrix maximum entropy method" (MxMEM), which offers efficient signal-to-noise ratio (SNR) enhancement of multidimensional spectral data. MxMEM is based upon two previous regularization methods that employ the maximum entropy concept. The first is a one-dimensional (1D) algorithm, which smoothes individual vectors, called the two-point maximum entropy method (TPMEM). The second is a two-dimensional (2D) form called 2D TPMEM, that smoothes images hut processes them one vector at a time. MxMEM is a truly two dimensional image processing algorithm in that its "smoothing engine" performs two-dimensional processing in every iteration. We demonstrate that this matrix-based construction makes more effective use of two-dimensionally embedded information and thus confers significant advantages over other regularization approaches. In addition, we utilize the concept that individual related Raman spectra can be combined in a matrix to form an artificial Raman "image". We show that, when processed as an image, superior SNR enhancement is achieved compared to processing the same data by TPMEM one spectrum at a time.

关键词： Two-dimensional spectral smoothing Signal-to-noise ratio enhancement SNR Two-dimensional regularization image processing algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：