Hierarchical and Wavelet-Based Multilinear Models for Multi-Dimensional Visual Data Approzimation

摘要：

1. Hierarchical Tensor Approximation With advances in imaging technologies--such as CCD, laser, magnetic resonance, and diffusion tensor---visual data of multiple dimensions have been produced at an unprecedented rate and scale. These new technologies bring new challenges to existing multidimensional image compression techniques. Visual data exhibit two important intertwined characteristics. First, they comprise of signals at many different frequencies. Second, these signals have spatially inhomogeneous magnitudes. Existing techniques, such as wavelet transforms, have successfully exploited both of the aforementioned characteristics to achieve a transformation that is local in both frequency and space domains. As a result of such transformation, the inherent structures of the original signal become better exposed to compression.

作者: Yizhou Yu

作者单位: University of Illinois at Urbana-Champaign

会议类型: 国际会议

会议名称: 11th IEEE International Conference on Computer-Aided Design and Computer Graphics(第11届IEEE国际计算机辅助设计与图形学学术会议 IEEE CAD/GRAPHICS 2009)

会议地点: 黄山

会议语种:英文

页码: 28-29

在线出版日期: 2009-08-19（万方平台首次上网日期，不代表论文的发表时间）