J. Díaz-García, P. Brunet, I. Navazo, Pere-Pau Vázquez
{"title":"Downsampling and Storage of Pre-Computed Gradients for Volume Rendering","authors":"J. Díaz-García, P. Brunet, I. Navazo, Pere-Pau Vázquez","doi":"10.2312/CEIG.20171208","DOIUrl":null,"url":null,"abstract":"The way in which gradients are computed in volume data-sets influences both the quality of the shading and the performance obtained in rendering algorithms. In particular, the visualization of coarse datasets in multi-resolution representations is affected when gradients are evaluated on-the-fly in the shader code by accessing neighbouring positions. We propose a downsampling filter for pre-computed gradients that provides improved gradients that better match the originals such that the aforementioned artifacts disappear. Secondly, to address the storage problem, we present a method for the efficient storage of gradient directions that is able to minimize the minimum angle achieved among all representable vectors in a space of 3 bytes.","PeriodicalId":385751,"journal":{"name":"Spanish Computer Graphics Conference","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spanish Computer Graphics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/CEIG.20171208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The way in which gradients are computed in volume data-sets influences both the quality of the shading and the performance obtained in rendering algorithms. In particular, the visualization of coarse datasets in multi-resolution representations is affected when gradients are evaluated on-the-fly in the shader code by accessing neighbouring positions. We propose a downsampling filter for pre-computed gradients that provides improved gradients that better match the originals such that the aforementioned artifacts disappear. Secondly, to address the storage problem, we present a method for the efficient storage of gradient directions that is able to minimize the minimum angle achieved among all representable vectors in a space of 3 bytes.