{"title":"基于帧一致性的图像有序平行体光线投射","authors":"Sukhyun Lim, Daesung Lee, B. Shin","doi":"10.1109/ICISA.2011.5772418","DOIUrl":null,"url":null,"abstract":"For an efficient parallel volume ray casting suitable for recent multi-core CPUs, we propose an image-ordered approach by using a cost function to allocate loaded tasks impartially per each processing node. At the first frame, we divide an image space evenly, and we compute a cost function. By applying the frame coherence property, we divide the image space unevenly using the computed previous cost function since the next frame. Conventional image-ordered parallel approaches have focused on dividing and compositing volume datasets. However, the divisions and accumulations are negligible for recent multi-core CPUs because they are performed inside one physical CPU. As a result, we can reduce the rendering time without deteriorating the image quality by applying a cost function reflecting on all time-consuming steps of the volume ray casting.","PeriodicalId":425210,"journal":{"name":"2011 International Conference on Information Science and Applications","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Image-Ordered Parallel Volume Ray Casting Using Frame Coherence\",\"authors\":\"Sukhyun Lim, Daesung Lee, B. Shin\",\"doi\":\"10.1109/ICISA.2011.5772418\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For an efficient parallel volume ray casting suitable for recent multi-core CPUs, we propose an image-ordered approach by using a cost function to allocate loaded tasks impartially per each processing node. At the first frame, we divide an image space evenly, and we compute a cost function. By applying the frame coherence property, we divide the image space unevenly using the computed previous cost function since the next frame. Conventional image-ordered parallel approaches have focused on dividing and compositing volume datasets. However, the divisions and accumulations are negligible for recent multi-core CPUs because they are performed inside one physical CPU. As a result, we can reduce the rendering time without deteriorating the image quality by applying a cost function reflecting on all time-consuming steps of the volume ray casting.\",\"PeriodicalId\":425210,\"journal\":{\"name\":\"2011 International Conference on Information Science and Applications\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Information Science and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISA.2011.5772418\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Information Science and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISA.2011.5772418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Image-Ordered Parallel Volume Ray Casting Using Frame Coherence
For an efficient parallel volume ray casting suitable for recent multi-core CPUs, we propose an image-ordered approach by using a cost function to allocate loaded tasks impartially per each processing node. At the first frame, we divide an image space evenly, and we compute a cost function. By applying the frame coherence property, we divide the image space unevenly using the computed previous cost function since the next frame. Conventional image-ordered parallel approaches have focused on dividing and compositing volume datasets. However, the divisions and accumulations are negligible for recent multi-core CPUs because they are performed inside one physical CPU. As a result, we can reduce the rendering time without deteriorating the image quality by applying a cost function reflecting on all time-consuming steps of the volume ray casting.