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remote sensing processing: From Multicore to GPU

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND remote sensing 2011年第3期4卷 643-652页

作者： Christophe, Emmanuel Michel, Julien Inglada, Jordi Natl Univ Singapore CRISP Singapore 119260 Singapore Commun & Syst CS F-31506 Toulouse France CNES Ctr Etud Spatiales BIOsphere CESBIO F-31401 Toulouse France

As the amount of data and the complexity of the processing rise, the demand for processing power in remote sensing applications is increasing. The processing speed is a critical aspect to enable a productive interaction between the human operator and the machine in order to achieve ever more complex tasks satisfactorily. Graphic processing units (GPU) are good candidates to speed up some tasks. With the recent developments, programing these devices became very simple. However, one source of complexity is on the frontier of this hardware: how to handle an image that does not have a convenient size as a power of 2, how to handle an image that is too big to fit the GPU memory? This paper presents a framework that has proven to be efficient with standard implementations of image processing algorithms and it is demonstrated that it also enables a rapid development of GPU adaptations. Several cases from the simplest to the more complex are detailed and illustrate speedups of up to 400 times.

关键词： CUDA GPU implementation OpenCL

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recent developments in High Performance Computing for remote sensing: A Review

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND remote sensing 2011年第3期4卷 508-527页

作者： Lee, Craig A. Gasster, Samuel D. Plaza, Antonio Chang, Chein-, I Huang, Bormin Univ Extremadura Hyperspectral Comp Lab Dept Technol Comp & Commun Caceres 10003 Spain Aerosp Corp Comp Syst Res Dept El Segundo CA 90245 USA Univ Maryland Baltimore Cty Dept Comp Sci & Elect Engn Remote Sensing Signal & Image Proc Lab Baltimore MD 21250 USA Natl Chung Hsing Univ Dept Elect Engn Taichung 402 Taiwan Univ Wisconsin Space Sci & Engn Ctr Madison WI 53706 USA

remote sensing data have become very widespread in recent years, and the exploitation of this technology has gone from developments mainly conducted by government intelligence agencies to those carried out by general users and companies. There is a great deal more to remote sensing data than meets the eye, and extracting that information turns out to be a major computational challenge. For this purpose, high performance computing (HPC) infrastructure such as clusters, distributed networks or specialized hardware devices provide important architectural developments to accelerate the computations related with information extraction in remote sensing. In this paper, we review recent advances in HPC applied to remote sensing problems;in particular, the HPC-based paradigms included in this review comprise multiprocessor systems, large-scale and heterogeneous networks of computers, grid and cloud computing environments, and hardware systems such as field programmable gate arrays (FPGAs) and graphics processing units (GPUs). Combined, these parts deliver a snapshot of the state-of-the-art and most recent developments in those areas, and offer a thoughtful perspective of the potential and emerging challenges of applying HPC paradigms to remote sensing problems.

关键词： Cloud distributed computing infrastructures (DCIs) field programmable gate arrays (FPGAs) graphics processing units (GPUs) grids high performance computing (HPC) multiprocessor systems remote sensing applications service architectures specialized hardware architectures

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Utility assessment of a multispectral snapshot LWIR imager

Utility assessment of a multispectral snapshot LWIR imager

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Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS

作者： Jeffrey Mercier Toby Townsend Robert Sundberg Sandia National Laboratories USA Spectral Sciences Inc. USA

The purpose of this study was to asses the utility of a Long Wave Infrared (LWIR) snapshot imager for remote sensing applications. The snapshot imager is made possible by the utilization of a color filter array that selectively allows different wavelengths of light to be collected on separate pixels of the focal plane in same fashion as a typical Bayer array in visible portion of the spectrum. recent technology developments have made this possible in the LWIR. The primary focus of the study is to develop a band selection technique that is capable of identifying both the optimal number and width of the spectral channels. Once selected, the theoretical sensor performance is used to evaluate the usefulness in a typical remote sensing application.

关键词： Arrays Measurement Materials image color analysis Hyperspectral sensors Optical filters

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remote sensing for management of solar geomagnetic disturbances on power system

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International Journal of Earth Sciences and Engineering 2010年第SPECIAL ISSUE期3卷 45-54页

作者： Naidu, Hari Kumar Thanushkodi, K. Electrical and Electronics Engineering Adhiyamaan college of Engineering Dr.M.G.R.Nagar Hosur-635109 TamilNadu India Akshaya College of Engineering and Technology Bagavathipalayam Road Kinathukadavu Coimbatore TamilNadu India

The recent developments in the field of remote sensing with its wide spectrum of sensor systems provide opportunity to gather information on solar wind, solar flares and other solar phenomena occurring in space as well as high geological resistivity areas consisting of igneous rock formation on earth by Geographical information system, in space and time domain for vast range of scientific discipline. India has made most significant contribution by developing state of art sensor systems, building launch capabilities of remote sensing series satellites & developing applications needed for national development. With judicious combination of satellite data sets with GIS, it is possible to carry out detailed mapping and correlating advanced digital image processing techniques like artificial intelligence & neural network, which may further improve the accuracy of the derived thematic layers from satellite image for forecasting effects of solar Geo magnetic disturbances on power systems and transformers reliably. This paper will present the causes and nature of geomagnetic storms & their resulting effects on Electrical power system to reliably operate since the solar flares can cause transient fluctuations in the earth's magnetic field. © 2010 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.

关键词： remote sensing

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recent developments in morphological image processing for remote sensing

Recent developments in morphological image processing for re...

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image and Signal processing for remote sensing XV

作者： Soille, Pierre Joint Research Centre Institute for Protection and Security of Citizen European Commission via Fermi 2749 I-21027 Ispra Italy

ISBN: (纸本)9780819477828

This paper highlights a series of recent developments in morphological image processing that are of interest for the analysis of remote sensing data. Each selected development is briefly presented while emphasising its usefulness in the context of real applications. The following topics are covered: grey level hit-or-miss transforms applied to the detection of specific man-made structures in panchromatic images, iterative area filtering for multichannel image simplification, constrained connectivity applied to hierarchical image partitioning of very high resolution images, mosaicing of an arbitrary number of images by automatically finding seam lines following salient image structures, and morphological segmentation of binary patterns applied to the characterisation of land cover classes. The paper concludes with challenges ahead and an open question. © 2009 SPIE.

关键词： Mathematical morphology

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remote sensing of Mountain Environments

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GEOGRAPHY COMPASS 2009年第1期3卷 1-21页

作者： Weiss, Daniel J. Walsh, Stephen J. Univ N Carolina Dept Geog Chapel Hill NC 27599 USA

Logistical challenges of conducting field research in topographically complex alpine settings, combined with the multi-scale and multi-thematic informational needs of earth and landscape scientists and program managers, have contributed to the development and application of remote sensing data, methods, and approaches for the study of mountain environments. This article provides a brief introduction to remote sensing science;illustrates specific challenges unique to remote sensing applications in mountainous environments, along with corresponding solutions;provides several examples of remote sensing applications in the alpine treeline ecotone;and concludes by describing recent and anticipated remote sensing developments that have the potential to improve characterizations of alpine settings through satellite surveillance techniques linked to image processing and analysis.

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Spectral derivative feature coding for hyperspectral signature analysis

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Pattern Recognition 2009年第3期42卷 395-408页

作者： Chang, Chein-I Chakravarty, Sumit Chen, Hsian-Min Ouyang, Yen-Chieh Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Environmental Restoration and Disaster Reduction Research Center National Chung Hsing University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Radiology China Medical University Hospital Taichung Taiwan

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC. © 2008 Elsevier Ltd. All rights reserved.

关键词： Spectrum analysis

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The Local Binary Pattern Approach and its applications to Face Analysis

The Local Binary Pattern Approach and its Applications to Fa...

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1st International Workshop on image processing Theory

作者： Hadid, Abdenour Univ Oulu Machine Vis Grp FI-90014 Oulu Finland

ISBN: (纸本)9781424433216

The local binary pattern (LBP) operator is defined as a gray-scale invariant texture measure, derived from a general definition of texture in a local neighborhood. Due to its discriminative power and computational simplicity, the LBP texture operator has become a popular approach in various applications, including visual inspection, image retrieval, remote sensing, biomedical image analysis, motion analysis, environment modelling, and outdoor scene analysis. recent developments showed that the local binary pattern texture method also provides outstanding results in representing and analyzing faces in both still images and video sequences. This paper describes the tutorial that will be lectured at The International Workshops on image processing Theory, Tools and applications (IPTA'08) and presents an overview of applying LBP approach to various face analysis related tasks, including eye detection, face recognition, face detection, facial expression recognition, visual-speech recognition and gender classification.

关键词： Local binary pattern

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The Local Binary Pattern Approach and its applications to Face Analysis

The Local Binary Pattern Approach and its Applications to Fa...

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Workshops on image processing Theory, Tools and applications, IPTA

作者： Abdenour Hadid Machine Vision Group University of Oulu Finland

关键词： Pattern analysis image analysis Face detection Face recognition image texture analysis image recognition Gray-scale Biomedical measurements Biomedical computing Inspection

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recent developments and future directions in hyperspectral data classification

Recent developments and future directions in hyperspectral d...

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Conference on image and Signal processing for remote sensing XIII

作者： Plaza, Antonio J. Univ Extremadura Dept Technol Comp & commun E-10071 Caceres Spain

ISBN: (纸本)9780819469069

Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than 30 years from being a sparse research tool into a commodity product available to a broad user community. As a result, there is an emerging need for standardized data processing techniques, able to take into account the special properties of hyperspectral data and to take advantage of latest-generation sensor instruments and computing environments. The goal of this paper is to provide a seminal view on recent advances in techniques for hyperspectral data classification. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data. and to integrate the spatial and spectral information. The performance of the proposed techniques is evaluated in different analysis scenarios, including land-cover classification, urban mapping and spectral unmixing. To satisfy time-critical constraints in many remote sensing applications, parallel implementations for some of the discussed algorithms are also developed. Combined, these parts provide a snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on the potential and emerging challenges in the design of robust hyperspectral data classification algorithms.

关键词： hyperspectral data classification mathematical morphology support vector machines intelligent training sample selection algorithms spectral mixture analysis parallel processing

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