A Spectral Graph Theory Approach for Data Re-mapping
Interactive navigation of large high-dimensional media datasets aims at allowing viewers to freely navigate content, selecting a subset of the high-dimensional visual data of interest for display. An example application would be remote visualization of an arbitrary 2-D planar cut from a large volumetric dataset with random access. In our previous work, we proposed a clientserver based data representation and retrieval system using overlapping rotated tiles to represent the dataset, which leads to lower bandwidth required for accessing a random plane from large volume data. This leads to the question of how best to represent these rotated tiles for compression. We have presented a non-interpolated symmetric mapping algorithm, which maps each voxel in the original image to a rotated Cartesian grid point. In this paper, we will present a tool to analyze and quantify the performance and demonstrate the benefits of our proposed re-mapping algorithm. We will show that in general the more symmetric the mapping is, the better RD performance can be achieved. Our analysis, based on spectral graph theory, could be used for measuring the performance of different mapping algorithms on a grid of any dimension.
Zihong Fan Antonio Ortega
Signal and Image Processing Institute Ming Hsieh Department of Electrical Engineering University of Signal and Image Processing InstituteMing Hsieh Department of Electrical EngineeringUniversity of So
国际会议
2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)
西安
英文
1-5
2011-10-18（万方平台首次上网日期，不代表论文的发表时间）