Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.最新文献

{"title":"Overview of Hyperion on-orbit instrument performance, stability, and artifacts","authors":"D. Beiso","doi":"10.1109/AIPR.2002.1182260","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182260","url":null,"abstract":"Hyperion, one of three payloads on the Earth-Observing 1 (EO-1) spacecraft that was launched from Vandenberg Air Force Base on November 21, 2000, is a hyperspectral imager built by TRW Space & Electronics for NASA's Goddard Space Flight Center. EO-1 is part of NASA's New Millennium Program whose goal is to demonstrate advanced technologies for reducing cost and improving quality of instruments and spacecraft for future space missions. Under this program, missions are intended primarily to validate new technologies in-flight and to provide useful data to the scientific research community. The first four months of mission life were focused on instrument activation, functional checkout, and performance verification. This paper presents an overview of the Hyperion instrument, summarize the on-orbit performance verification and validation activities, and describe known instrument artifacts.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133823584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data","authors":"M. Matthew, S. Adler-Golden, A. Berk, G. Felde, G. Anderson, D. Gorodetzky, S. Paswaters, M. Shippert","doi":"10.1109/AIPR.2002.1182270","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182270","url":null,"abstract":"With its combination of good spatial and spectral resolution, visible to near infrared spectral imaging from aircraft or spacecraft is a highly valuable technology for remote sensing of the Earth's surface. Typically it is desirable to eliminate atmospheric effects on the imagery, a process known as atmospheric correction. We review the basic methodology of first-principles atmospheric correction and present results from the latest version of the FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes) algorithm. We show some comparisons of ground truth spectra with FLAASH-processed AVIRIS (airborne visible/infrared imaging spectrometer) data, including results obtained using different processing options, and with results from the ACORN (atmospheric correction now) algorithm that derive from an older MODTRAN4 spectral database.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"68 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113962398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From X-rays to radar: using color to understand imagery","authors":"E. Williams, Carlos Maraviglia","doi":"10.1109/AIPR.2002.1182256","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182256","url":null,"abstract":"This paper discusses the problems of collecting and processing imagery across the electromagnetic spectrum from X-rays to radar. The authors in this overview paper start at the short wave length part of the spectrum and go through the spectrum (X-rays) to the longer wavelength and synthetic aperture radar (SAR) imagery and describe the problems of collecting imagery and understanding this imagery. The sub bands of the spectrum that are discussed include X-rays, ultraviolet, visible images from violet to red, the infrared bands including short wave, mid wave, and long wave, the millimeter wave, and the meter wavelength or SAR images. The use of color or using multiple sub bands at each part of the spectrum to improve image understanding are described. The advantages of using color and the problems of collecting color imagery in each part of the spectrum are discussed in this paper. Examples are given of the sensors, the images, and the color image processing required to understand these images. Other factors such as special resolution obtainable in each sub band, amount of human intervention required to understand the imagery, and number of bands to collect and process versus improvement in understanding of the images are also be described.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122734262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyperspectral imaging of Kaposi's Sarcoma for disease assessment and treatment monitoring","authors":"D. Hattery, Moinuddin Hassan, S. Demos, A. Gandjbakhche","doi":"10.1109/AIPR.2002.1182265","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182265","url":null,"abstract":"Light spectroscopic methods are critical to advances in molecular characterization of disease processes. However, these methods have been limited to in-vitro or cell culture studies. In fact, strong scattering in almost all tissue types causes dispersion of the photons paths which results in poor localization and resolution. Hence, quantitative analysis of spectral data obtained from structures below the tissue surface requires accounting for scattering which affects both the penetration of the photons and the path length over which the photons will be subject to molecularly specific absorption. The goal of much current research is to non-invasively obtain diagnostically useful molecular information from embedded sites. We have designed and built a six-band multi-spectral NIR imaging system which we have used on patients with highly vascularized tumors in the skin called Kaposi's Sarcoma. The imaged lesions are undergoing treatment with experimental anti-angiogenesis drugs that are designed to reduce bloodflow and hence growth of the tumors. The NIR data is combined with both 3-5 micron and 8-12 micron infrared images, obtained of the same tumors, which are used to identify thermal signatures of blood volume, as well as three-band visible wavelength data which show the visible extent of the lesions. We have developed a layered model of the skin in which specific analytes exist in specific layers. The spectral signatures of analytes such as oxy- and deoxy-hemoglobin are known. To obtain information on the concentration of those analytes in the tissue, however, the diffuse reflectance NIR images from the patients must be corrected for scattering. The scattering is modeled using analytical solutions developed from a random walk model of photon migration in turbid media. When the hyperspectral patient data is fit to the model, physiologically related parameters, such as to blood volume and oxygenation, are obtained. This provides clinically important data that may be used by the physician for evaluations of drug effectiveness, disease assessment and patient treatment monitoring.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115137861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic target detection using multispectral imaging","authors":"Bilge Karaçali, W. Snyder","doi":"10.1109/AIPR.2002.1182255","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182255","url":null,"abstract":"We propose using multispectral imaging for on-the-fly target detection and classification instead of hyperspectral imaging. We initially pose the target detection problem as a classification problem with classes identified as target and clutter. The classification data consists of multispectral observations of the region of interest, focusing on visual and infrared wavelengths. We then solve this classification problem using nearest neighbor rule, support vector machines, and maximum likelihood classification. Simulation results on real data indicate that information from a multispectral sensor can offer better performance than both single band and hyperspectral sensors, also showing that costly hyperspectral analysis performance can be attained onboard a small airborne platform such as a smart missile using cost-effective multispectral sensors.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124756370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hand held imaging spectrometer","authors":"M. Hinnrichs","doi":"10.1109/AIPR.2002.1182258","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182258","url":null,"abstract":"A small hand held, battery operated imaging infrared spectrometer, Sherlock, has been developed by Pacific Advanced Technology. The Sherlock spectral imaging camera has been designed for remote gas leak detection, however, the architecture of the camera is versatile enough that it can be applied to numerous other applications such as homeland security, chemical/biological agent detection, medical and pharmaceutical applications, as well as standard research and development. This paper describes the Sherlock camera, theory of operation, shows current applications and touches on potential future applications for the camera. The Sherlock has an embedded Power PC and performs real-time-image processing function in an embedded FPGA. It has several I/O ports, Ethernet, FireWire, RS232 and thus can be easily controlled from a remote location. In addition, software upgrades can be performed over the Ethernet eliminating the need to send the camera back to the factory for a retrofit. Using the USB port a mouse and key board can be connected and the camera can be used in a laboratory environment as a stand alone imaging spectrometer.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131799560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Onboard processor for compressing HSI data","authors":"S. Cook, J. Harsanyi","doi":"10.1109/AIPR.2002.1182277","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182277","url":null,"abstract":"As HSI (hyperspectral imaging) sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and in developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), which has extensive heritage in HSI, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor >100, while retaining the necessary spectral fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our spectral compression technique leverages commercial-off-the-shelf (COTS) spectral exploitation algorithms for segmentation, material identification and spectral compression that ASIT has developed. Other commercially available COTS software for spatial compression will also be employed as part of the overall compression processing sequence.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132257336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of LWIR polarimetric observations of space objects","authors":"M. Pesses, John Tan, Ryan Hash, R. Swartz","doi":"10.1109/AIPR.2002.1182271","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182271","url":null,"abstract":"SAIC's 3D LWIR spectropolarimetric signature model, Polar Heat, is used to simulate LWIR polarimetric observations of space objects. Both imaging and nonimaging simulated observations are presented for spinning and tumbling satellites, as well as RVs (reentry vehicles) and decoys. Polar Heat is a 1/sup st/ principle model that extends microfacet-based scattering models from intensity to polarimetric using a computational approach that utilizes the Born Wolf coherence matrix to integrate reflected and self-emitted radiation seamlessly. Thermal self-emission is transmitted internal blackbody radiation that is modified by passing through the change in the index of refraction that occurs at the surface-space interface. Polar Heat includes Fresnel and \"BRDF\" interactions, as well as incoherent scattering, shadowing, obscuration, terrestrial and space emissions and CAD target objects. Multi-bounce and atmospheric transport effects are neglected in the results presented. Initial simulations suggest that polarimetric observations could provide a more sensitive way to detect and identify space objects.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114569381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lippmann photography and the glory of frozen light: eternal photographic color real and false","authors":"W. Alschuler","doi":"10.1109/AIPR.2002.1182248","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182248","url":null,"abstract":"Lippmann photography is a 110-year old process that offers full color images on black and white recording media. The process was never commercialized. The author reviews the history of the process, its historical context, current work on the process and some of the problems encountered with it. The author suggests a number of applications which take advantage of the Lippmann process characteristics within its limitations. Examples of historic and recent images are shown.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121289606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An architecture for sensor data fusion target tracking","authors":"R. Bonneau, J. Perretta, B. Rahn, Mark D. Barnell","doi":"10.1109/AIPR.2002.1182274","DOIUrl":"https://doi.org/10.1109/AIPR.2002.1182274","url":null,"abstract":"Many geographic target tracking scenarios provide difficult geospatial environments for collecting reliable sensor data. As a result, multiple sensor data sources must be integrated to provide a reliable estimate of an object's position as it moves through various environments. We describe MTI-Net, a geospatial database dedicated to providing reliable sensor data for an object moving through various geospatial environments by integrating multiple sensor data sources together in a Web-based environment. MTI-Net is an integration of database and signal processing resources.","PeriodicalId":379110,"journal":{"name":"Applied Imagery Pattern Recognition Workshop, 2002. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130844176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}