{"title":"基于异构OPENVISION并行计算机的卫星数字高程模型","authors":"H. Essafi, C. Mazzoni, P. Julien, O. Jamet","doi":"10.1109/CAMP.1995.521072","DOIUrl":null,"url":null,"abstract":"The goal of the Digital Elevation Model is to generate an accurate three-dimensional scene using a stereo vision technique. In the stereo matching process two techniques are utilized, an area-based and feature-based to generate a disparity map. In our application we use an area-based approach coupled with the prediction validation techniques. The computation of the Digital Elevation Model (DEM) is based on correlation, also called matching, to determine the pixel correspondence in a pair of stereo spatial images. It is a fundamental step in digital mapping. The French \"Institut Geographique National\" (IGN) has developed a system to provide DEM. The kernel of this system is based on an incremental correlation method, which is the bottleneck in the map production because of its expenditure of computing time. In the same way the CEA-LETI has developed in collaboration with the IRIT laboratory (Toulouse University), a SIMD calculator SYMPATI2 dedicated to image processing, and integrated in the OPENVISION real-time system. The IGN DEM of SPOT images (6000/spl times/6000) takes 20 hours using a Sparc 10 workstation. In order to reduce this computation time we studied the parallelization and the implementation the IGN algorithm on OPENVISION.","PeriodicalId":277209,"journal":{"name":"Proceedings of Conference on Computer Architectures for Machine Perception","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Satellite Digital Elevation Model on the heterogeneous OPENVISION parallel computer\",\"authors\":\"H. Essafi, C. Mazzoni, P. Julien, O. Jamet\",\"doi\":\"10.1109/CAMP.1995.521072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of the Digital Elevation Model is to generate an accurate three-dimensional scene using a stereo vision technique. In the stereo matching process two techniques are utilized, an area-based and feature-based to generate a disparity map. In our application we use an area-based approach coupled with the prediction validation techniques. The computation of the Digital Elevation Model (DEM) is based on correlation, also called matching, to determine the pixel correspondence in a pair of stereo spatial images. It is a fundamental step in digital mapping. The French \\\"Institut Geographique National\\\" (IGN) has developed a system to provide DEM. The kernel of this system is based on an incremental correlation method, which is the bottleneck in the map production because of its expenditure of computing time. In the same way the CEA-LETI has developed in collaboration with the IRIT laboratory (Toulouse University), a SIMD calculator SYMPATI2 dedicated to image processing, and integrated in the OPENVISION real-time system. The IGN DEM of SPOT images (6000/spl times/6000) takes 20 hours using a Sparc 10 workstation. In order to reduce this computation time we studied the parallelization and the implementation the IGN algorithm on OPENVISION.\",\"PeriodicalId\":277209,\"journal\":{\"name\":\"Proceedings of Conference on Computer Architectures for Machine Perception\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Conference on Computer Architectures for Machine Perception\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMP.1995.521072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Conference on Computer Architectures for Machine Perception","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMP.1995.521072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
数字高程模型的目标是使用立体视觉技术生成精确的三维场景。在立体匹配过程中,采用了基于区域和基于特征的两种技术来生成视差图。在我们的应用程序中,我们使用了基于区域的方法以及预测验证技术。数字高程模型(DEM)的计算基于相关性,也称为匹配,以确定一对立体空间图像中的像素对应关系。这是数字制图的基本步骤。法国国家地理研究所(IGN)开发了一个提供DEM的系统。该系统的核心是基于增量相关法,而增量相关法耗费大量的计算时间,成为地图生成的瓶颈。同样,CEA-LETI与IRIT实验室(图卢兹大学)合作开发了SIMD计算器SYMPATI2,专门用于图像处理,并集成在OPENVISION实时系统中。使用Sparc 10工作站计算SPOT图像的IGN DEM (6000/spl次/6000)需要20小时。为了减少这种计算时间,我们研究了并行化算法,并在OPENVISION上实现了IGN算法。
Satellite Digital Elevation Model on the heterogeneous OPENVISION parallel computer
The goal of the Digital Elevation Model is to generate an accurate three-dimensional scene using a stereo vision technique. In the stereo matching process two techniques are utilized, an area-based and feature-based to generate a disparity map. In our application we use an area-based approach coupled with the prediction validation techniques. The computation of the Digital Elevation Model (DEM) is based on correlation, also called matching, to determine the pixel correspondence in a pair of stereo spatial images. It is a fundamental step in digital mapping. The French "Institut Geographique National" (IGN) has developed a system to provide DEM. The kernel of this system is based on an incremental correlation method, which is the bottleneck in the map production because of its expenditure of computing time. In the same way the CEA-LETI has developed in collaboration with the IRIT laboratory (Toulouse University), a SIMD calculator SYMPATI2 dedicated to image processing, and integrated in the OPENVISION real-time system. The IGN DEM of SPOT images (6000/spl times/6000) takes 20 hours using a Sparc 10 workstation. In order to reduce this computation time we studied the parallelization and the implementation the IGN algorithm on OPENVISION.