Recently, similarity queries on feature vectors have been widely used to perform content-based retrieval of images. To apply this technique to large databases, it is required to develop multidimensional index structures supporting nearest neighbor queries e ciently. The SS-tree had been proposed

virtual hexagonal structure that is scalable. Based on this virtual structure, algorithms for uni-form image separation are presented. The virtual hexagonal structure retains image resolution during the process of image separation, and does not intro-duce distortion. Furthermore, images can be smoothly

where the virtual machines transparently share major data structures such as the program code and the file system buffer cache. We use the distributed system support of modern operating systems to export a partial single system image to the users. The overall solution achieves most of the benefits

interpolation, Spiral Architecture, image processing, hexagonal structure.

in interactive virtual environments. The spatial subdivision is a partition of 3D space into convex polyhedral regions (cells) represented as a cell adjacency graph. A beam tracing algorithm recursively traces pyramidal beams through the spatial subdivision to construct a beam tree data structure representing

seband filter H(!) is that expression (1) have a value of unity for all !. Finally, these systems may be cascaded uniformly or non-uniformly (to form pyramid structures). Unlike traditional Gaussian or Laplacian pyramids, the representation is not overcomplete and may contain oriented subbands. We

;real virtuality'. Our symbolic environment is, by and large, structured by this exible, inclusive hypertext, in which many people surf each day. The virtuality of this text is in fact a fundamental dimension of reality, providing the symbols and icons from which we think and thus exist. This growing

that indicates that data structures based on hexagonal lattices may be a superior alternative for efficient representation and processing of raster and vector data in high performance applications. The advantages of hexagonal rasters for image processing are discussed, and hexagonal discrete global grid systems

, the transform boasts efficient lattice structures, which employ a minimal number of delay elements and are robust under the quantization of lattice coefficients. The resulted compression algorithm also retains all attractive properties of the EZW coder and its variations such as progressive image transmission

Spiral Architecture (SA) is a novel image structure which has hexagons but not squares as the basic elements. Apart from many other advantages in image processing, SA has shown two unbeatable characters that have potential to improve image compression performance, namely, Locality of Pixel Density