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Proceedings 29th applied imagery pattern recognition workshop

Proceedings 29th Applied Imagery Pattern Recognition Worksho...

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applied imagery pattern recognition workshop (AIPR)

Presents the front cover of the proceedings record.

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Proceedings - applied imagery pattern recognition workshop

Proceedings - Applied Imagery Pattern Recognition Workshop

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29th applied imagery pattern recognition workshop, AIPR 2000

ISBN: (纸本)0769509789

the proceedings contain 37 papers. the topics discussed include: early history of remote sensing;a harbor, a bomb, a wall-geopolitical context and the emergence of America's national reconnaissance imaging capability;orbital remote sensing of the earth's surface: a review;combining image derived spectra and physics based models for hyperspectral image exploitation;confronting clouds: detection, remediation and simulation approaches for hyperspectral remote sensing systems;automated road extraction via the hybridization of self-organization and model based techniques;volumetric optical storage and associative/context-based retrieval;ultra-high transfer rate high capacity holographic disk digital data storage system;parallel associative search by use of a volume holographic memory;optically reconfigurable gate array;and image retrieval with relevance feedback.

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Rapid data reduction and target detection in literal imagery 29

Rapid data reduction and target detection in literal imagery

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29th applied imagery pattern recognition workshop

作者： Hoogs, A Mundy, J GE Corp Res & Dev Niskayuna NY 12309 USA

ISBN: (纸本)0769509789

Image compression rates can be greatly improved without significant information loss by detecting all target-like objects with a low-cost, focus-of-attention operator. Potential target regions are compressed with high fidelity, while background regions are compressed with high loss. In SAR imagery, target detection technology is relatively mature;however, in EO imagery intensity-based filters are not sufficient to separate targets from the background. Here we present a method to perform target detection in EO imagery by rapidly reducing imagery data volume as algorithmic complexity, increases. the technique is based on perceptual grouping of segmented regions through generic geometric, intensity and topology constraints that distinguish vehicles from the back-ground. At each of three processing stages, greater than 90% data reduction can be achieved, even at high false alarm rates. the typical compression ratio of the complete system can be very high while retaining virtually all significant information. the efficacy of the algorithm is demonstrated by experimental results on large reconnaissance images of wide-area battlefield scenes showing camouflaged vehicles in complex backgrounds.

关键词： Image enhancement

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Assessing the performance effects of data compression for SAR imagery 29

Assessing the performance effects of data compression for SA...

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29th applied imagery pattern recognition workshop

作者： Eckstein, BA Peters, R Irvine, JM Ritzel, R Hummel, R Sci Applicat Int Corp Mclean VA 22102 USA

ISBN: (纸本)0769509789

Although there are many ways to assess the impact of compression on image quality, in the final analysis one of the most important metrics is the impact of compression on end-users. this study evaluated compression effects on manual exploitation performed by military imagery analysis. the original SAR imagery and compressed products were rated for Radar NIIRS, image features, sensor artifacts, and target detection and recognition. JPEG, Wavelet/Trellis-Coded Quantization (W/TCQ), and Intelligent Bandwidth Compression (IBC) were tested at 50 and 100-to-1 ratios. this study found that the utility of the compressed imagery's utility differed only slightly from the original, except for the JPEG products. Otherwise, both 50 and 100-to-1 compressed imagery appeared similar in quality. Radar NIIRS indicates that even 100-to-1 compression using IBC or W/TCQ has minimal impact on imagery intelligence value. A slight loss in performance occurred for vehicle counting and identification tasks. these findings suggest that both Single Scale IBC and Wavelet/TCQ compression techniques have matured to a point that they could provide value to the tactical user. Additional assessments may verify the practical limits of compression for SAR data and address the transition to afield environment.

关键词： Quality control

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Combining image derived spectra and physics based models for hyperspectral image exploitation 29

Combining image derived spectra and physics based models for...

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29th applied imagery pattern recognition workshop

作者： Schott, JR Rochester Inst Technol Ctr Imaging Sci Rochester NY 14623 USA

ISBN: (纸本)0769509789

this paper addresses a conceptual approach to hyperspectral image assessment that uses physics-based models to constrain multiparameter inversion algorithms aimed at quantitative measurement of material properties. the new millennium will see a host of new sensing approaches that allow us to acquire many measurements of a target. these measurements may be in the form of;a single hyperspectral image with hundreds of spectral samples, a sequence of many images acquired over time from sensors with a few channels or widely different types of measurements from a range of sensor types (e.g., thermal, polarimetric, multispectral, radar...). We propose a conceptual approach for merging these data into a common framework to allow simultaneous exploitation of these multiparameter data sets. the approach uses physics-based models to predict or constrain the range of observable parameters associated with a target or material condition and then applies model matching or optimization methods to invert a measurement set to a target type or condition. In this paper, two examples are presented for this approach using hyperspectral data sets. the first involves characterizing atmospheric constituents (pressure depth, column water vapor amount and aerosol visibility) using the MODTRAN Code to constrain the solutions. the second involves using a radiation propagation model that includes atmospheric and aquatic propagation to drive an inversion of hyperspectral data to multiple water quality parameters (chlorophyll, suspended materials and yellowing organics). Finally, we close with a discussion of how more involved three-dimensional physics-based synthetic image models may hold a key to image exploitation algorithms in the new millennium.

关键词： remote sensing physics based models synthetic imagery hyperspectral imagery

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Wavelet/trellis coded quantization of complex SAR imagery 29

Wavelet/trellis coded quantization of complex SAR imagery

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29th applied imagery pattern recognition workshop

作者： Heermans, JM Rouse, R Chang, CF Bonneau, R Lockheed Martin Management & Data Syst Reconnaissance Syst Goodyear AZ 85338 USA

ISBN: (纸本)0769509789

Recent advancements in radar sensor technology and processing capabilities enable a large volume of data to be collected and made available to the war fighter. However, the bandwidth of data dissemination and storage is strained. Synthetic aperture radar (SAR) imagery, different from other remote sensors, is complex, containing not only magnitude but also phase components, i.e., two channels per pixel. this paper describes Lockheed Martin's wavelet/trellis coded quantization (W/TCQ) compression algorithm and presents results of quantitative assessment of the impact of data compression on complex SAR data. Compression performance was evaluated both quantitatively using statistical measurements and qualitatively by image analysts. Trade studies of various compression schemes and data formats were also investigated. Data distortion due to compression/decompression was assessed using statistical metrics such as signal-to-quantization noise ratio, RMS phase distortion, and ability to support subsequent complex data processing operations. Quantitative assessments were performed with error analyses and a simple decision function to address how data compression affects A TR performance. Data compression did not significantly reduce image utility for magnitude channel compression ratios of up to 64:1. On the other hand, the phase channel compression required 4 bits per pixel to allow adequate phase fidelity to support subsequent complex operations. Magnitude/phase representation afforded better compression results than representing the data in I/Q format. Should this finding remain consistent, it has a significant impact on the compression scheme employed in an operational scenario. the magnitude and phase channels can be allocated different compression ratios to maintain both high quality image interpretability and necessary phase fidelity.

关键词： compression complex SAR trellis coded quantization radar

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An agent-based architecture for distributed imagery & geospatial computing 29

An agent-based architecture for distributed imagery & geospa...

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29th applied imagery pattern recognition workshop, AIPR 2000

作者： Nolan, James J. Sood, Arun K. Simon, Robert George Mason University Center for Image Analysis Dept. of Computer Science FairfaxVA22030 United States

ISBN: (纸本)0769509789

Agent-based approaches have not yet been widely applied to highly complex, data intensive, large-scale information processing systems such as are found in the domain of imagery & geospatial computing. Such systems combine diverse and distributed types of imagery and geospatial data, and require collaboration from multiple experts and processing components. this paper gives a description of the design and implementation of the Agent-based imagery and Geospatial processing Architecture (AIGA). Our approach centers on the development of an ontology, light-weight agents, and an agent communication language for imagery & geospatial computing. AIGA agents cooperate with each other to answer specific queries and to efficiently manage distributed resources. Many of of the imagery & geospatial exploitation tasks that AIGA agents process are highly complex, with several processing steps involved. We describe in detail how the AIGA system is inherently parallel, thus allowing for parallel implementations of both new and legacy imagery & geospatial exploitation algorithms. Because this system is agent driven, the parallelism is highly dynamic, reconfigurable via the AIGA communication language, an XML-based specification called I-XML. these I-XML specifications are distributed and transformed by different AIGA agents in the system to achieve a scalable and manageable system design for collaboration and information management. We describe the details of AIGA, the I-XML specification, and our Java based prototype. © 2000 IEEE.

关键词： XML

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Shuttle radar topography mission overview

Shuttle radar topography mission overview

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applied imagery pattern recognition workshop (AIPR)

作者： J.L. Kretsch National Imagery and Mapping Agency Reston VA USA

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Shuttle radar topography mission overview 29

Shuttle radar topography mission overview

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29th applied imagery pattern recognition workshop, AIPR 2000

作者： Kretsch, Jeffrey L. National Imagery and Mapping Agency Mail Stop P-53 12310 Sunrise Valley Drive RestonVA20191-3449 United States

ISBN: (纸本)0769509789

In 1995, the DoD Joint Staff and the Intelligence Community recognized the need for a common understanding of the operational environment and that a major inhibitor was the lack of availability of digital terrain elevation data (DTED);which is vital to successful mission planning, operations and readiness. Elevation data provides a key ingredient to the readiness of our customers. Elevation data is one of three components of Foundation Data - Elevation data, Feature data, and imagery data. Numerous systems under the control of the United States Government will use this data. Traditional methods to produce elevation data are very expensive and time consuming and major cloud belts would never be completed with existing methods. the National imagery and Mapping Agency (NIMA) with National Aeronautical and Space Agency (NASA) and the Jet Propulsion Laboratory (JPL) sponsored the Shuttle Radar Topography Mission (SRTM) to use an interferometric technique to collect elevation data. SRTM was selected as the best method to supply nearly global, accurate elevation data. From 11-22 February 2000, the SRTM payload flew aboard NASA's Space Shuttle and collected highly specialized data that will allow us to increase the United States Government's coverage of vital and detailed DTED level 2 from less than 5% to 80% of the Earth's landmass. this exceeds results from nearly 30 years of prior efforts with a variety of systems working against persistent cloud cover worldwide. this vital contribution significantly increases the release of 3 arc-second spaced digital elevation data worldwide. this presentation describes the shuttle mission and its deliverables. © 2000 IEEE.

关键词： Earth (planet)

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A comparison between fully connected and deconvolutional layers for road segmentation from satellite imagery

A comparison between fully connected and deconvolutional lay...

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27th Southern African Universities Power Engineering Conference (SAUPEC) / 11th Robotics and Mechatronics Conference of South Africa (RobMech) / 29th Annual Symposium of pattern-recognition-Association-of-South-Africa (PRASA)

作者： Bhugwan, Dhruv Ranchod, Pravesh Klein, Richard Rosman, Benjamin Univ Witwatersrand Sch Comp Sci & Appl Math Johannesburg South Africa CSIR Mobile Intelligent Autonomous Syst Pretoria South Africa

ISBN: (纸本)9781728103693

Semantic segmentation using fully convolutional networks has quickly become a popular solution as they provide very accurate per pixel classification. However, the implementation of deconvolutional layers and their mechanics differ greatly to those of patch based segmentation using convolutional neural networks. Both techniques have been used for road segmentation from satellite imagery but never compared. thus we investigate the difference between fully connected and deconvolutional layers and provide an interpretation as to the correlation and differences between each methodology for road segmentation from satellite imagery.

关键词： fully convolutional networks segmentation convolutional neural networks

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