Sunil Prabhakar, D. Agrawal, A. E. Abbadi, Ambuj K. Singh, Terence R. Smith
{"title":"在并行磁盘上浏览和放置多分辨率图像","authors":"Sunil Prabhakar, D. Agrawal, A. E. Abbadi, Ambuj K. Singh, Terence R. Smith","doi":"10.1145/266220.266230","DOIUrl":null,"url":null,"abstract":"With rapid advances in computer and communication technologies, there is an increasing demand to build and maintain large image repositories. In order to reduce the demands on I/O and network resources, multiresolution representations are being proposed for the storage organization of images. Image decomposition techniques such as wavelets can be used to provide these multiresolution images. The original image is represented by several coefficients, one of them with visual similarity to the original image, but at a lower resolution. These visually similar coefficients can be thought of as thumbnails or icons of the original image. This paper addresses the problem of storing these multiresolution coefficients on disks so that thumbnail browsing as well as image reconstruction can be performed efficiently. Several strategies are evaluated to store the image coefficients on parallel disks. These strategies can be classified into two broad classes depending on whether the access pattern of the images is used in the placement. Disk simulation is used to evaluate the performance of these strategies. Simulation results are validated wivith results from experiments wivith real disks and are found to be in good agreement. The results indicate that significant performance improvements can be achieved with as few as four disks by placing image coefficients based upon browsing access patterns.","PeriodicalId":442608,"journal":{"name":"Workshop on I/O in Parallel and Distributed Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Browsing and placement of multiresolution images on parallel disks\",\"authors\":\"Sunil Prabhakar, D. Agrawal, A. E. Abbadi, Ambuj K. Singh, Terence R. Smith\",\"doi\":\"10.1145/266220.266230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With rapid advances in computer and communication technologies, there is an increasing demand to build and maintain large image repositories. In order to reduce the demands on I/O and network resources, multiresolution representations are being proposed for the storage organization of images. Image decomposition techniques such as wavelets can be used to provide these multiresolution images. The original image is represented by several coefficients, one of them with visual similarity to the original image, but at a lower resolution. These visually similar coefficients can be thought of as thumbnails or icons of the original image. This paper addresses the problem of storing these multiresolution coefficients on disks so that thumbnail browsing as well as image reconstruction can be performed efficiently. Several strategies are evaluated to store the image coefficients on parallel disks. These strategies can be classified into two broad classes depending on whether the access pattern of the images is used in the placement. Disk simulation is used to evaluate the performance of these strategies. Simulation results are validated wivith results from experiments wivith real disks and are found to be in good agreement. The results indicate that significant performance improvements can be achieved with as few as four disks by placing image coefficients based upon browsing access patterns.\",\"PeriodicalId\":442608,\"journal\":{\"name\":\"Workshop on I/O in Parallel and Distributed Systems\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on I/O in Parallel and Distributed Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/266220.266230\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on I/O in Parallel and Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/266220.266230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Browsing and placement of multiresolution images on parallel disks
With rapid advances in computer and communication technologies, there is an increasing demand to build and maintain large image repositories. In order to reduce the demands on I/O and network resources, multiresolution representations are being proposed for the storage organization of images. Image decomposition techniques such as wavelets can be used to provide these multiresolution images. The original image is represented by several coefficients, one of them with visual similarity to the original image, but at a lower resolution. These visually similar coefficients can be thought of as thumbnails or icons of the original image. This paper addresses the problem of storing these multiresolution coefficients on disks so that thumbnail browsing as well as image reconstruction can be performed efficiently. Several strategies are evaluated to store the image coefficients on parallel disks. These strategies can be classified into two broad classes depending on whether the access pattern of the images is used in the placement. Disk simulation is used to evaluate the performance of these strategies. Simulation results are validated wivith results from experiments wivith real disks and are found to be in good agreement. The results indicate that significant performance improvements can be achieved with as few as four disks by placing image coefficients based upon browsing access patterns.