一种大规模体数据压缩体绘制策略
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摘要
针对基于GPU的大规模体数据直接体绘制过程中遇到的显存不足的问题,提出了一种大规模体数据的压缩绘制策略.该策略结合小波变换和分类矢量量化进行数据压缩,采用基于GPU的光线投射算法进行绘制,在绘制时,只解压变换当前绘制所需要的极少数数据,并结合多分辨率绘制,实现实时交互.基于CUDA的实验表明:该压缩绘制策略有效解决了显存不足问题,并且在保证交互绘制帧率的前提下获得了较好的成像质量.
In order to solve the problem of video memory limitation during GPU-based visualization of large scale volume data,a compressing and rendering strategy was proposed.Volume data was compressed by combining wavelet transform with vector quantization algorithm,and then transferred to GPU totally.When rendering,a GPU-based ray casting algorithm was adopted and only few current needed data was decompressed and transformed.In order to realize real-time interactive visualization,a multi-resolution rendering method was designed.Experimental results based on CUDA show that this strategy can decrease the video memory consumption effectively and obtain better image quality while ensuring interactive rendering frame rate.
In order to solve the problem of video memory limitation during GPU-based visualization of large scale volume data,a compressing and rendering strategy was proposed.Volume data was compressed by combining wavelet transform with vector quantization algorithm,and then transferred to GPU totally.When rendering,a GPU-based ray casting algorithm was adopted and only few current needed data was decompressed and transformed.In order to realize real-time interactive visualization,a multi-resolution rendering method was designed.Experimental results based on CUDA show that this strategy can decrease the video memory consumption effectively and obtain better image quality while ensuring interactive rendering frame rate.
引文
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[2]CABRAL B,CAM N,FORAN J.Accelerated volume rendering andtomographic reconstruction using texture mapping hardware[C]//Proceedings of the 1994 Symposium on Volume Visualization.NewYork:ACM,1994:91-98,131.
[3]LEE B,YUN J,SEO J,et al.Fast high-quality volume ray castingwith virtual samplings[J].IEEE Transactions on Visualization andComputer Graphics,2010,16(6):1525-1532.
[4]CHEN Shi-hao,HAO Chong-yang.Interactive GPU-based volumerendering for medical image[C]//Proceedings of Biomedical Engineer-ing and Informatics.Washington DC:IEEE,2009:1-4.
[5]赵利平,肖德贵,李肯立,等.一种高效体数据压缩算法及其在地震数据处理中的应用[J].计算机辅助设计与图形学学报,2009,21(11):1606-1611.ZHAO Li-ping,XIAO De-gui,LI Ken-li,et al.An efficient in al-gorithm for large-scale volume data compression and its application inseismic data processing[J].Journal of Computer-Aided Design&Computer Graphics,2009,21(11):1606-1611.(In Chinese)
[6]GUTHE S,WAND M,GONSER J,et al.Interactive rendering oflarge volume data sets[C]//Proceedings of IEEE Visualization.Washington DC:IEEE,2002:53-60.
[7]罗月童,薛哗,刘晓平.基于GPU的多分辨率体数据重构和渲染[J].计算机辅助设计与图形学学报,2009,21(1):107-111.LUO Yue-tong,XUE Ye,LIU Xiao-ping.GPU based multi-resolu-tion volume data reconstruction and rendering[J].Journal of Com-puter-Aided Design&Computer Graphics,2009,21(1):107-111.(In Chinese)
[8]KO Chia-lin,LIAO Horng-shyang,WANG Tsai-pei,et al.Multi-resolution volume rendering of large time-varying data using video-based compression[C]//Proceedings of Visualization Symposium.Washington DC:IEEE,2008:135-142.
[9]孙圣和,陆哲明.矢量量化技术及应用[M].北京:科学出版社,2002:323-324.SUN Sheng-he,LU Zhe-ming.Technology and application of vectorquantization[M].Beijing:Science Press,2002:323-324.(In Chi-nese)
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