A novel algorithm for reducing redundancy of the massive spatial data

Gaussian pyramid framework (GPF) and Laplacian pyramid framework (LPF) are the two main frameworks used for transmission and structure of spatial image and geometric data. LPF is the main approach for progressive transmission of spatial image data. This paper discusses the issues in structure, transmission and storage efficiency of spatial data in the current spatially distributed visualization system. Later in the paper, a novel approach is introduced to query, structure and transfer spatial data base on the Laplacian pyramid framework. This new approach transforms the spatial image data into high-frequency and low-frequency data, builds (spatial) index for transformed frequency data within different ranges. By eliminating the data redundancy in different ranges, this approach decreases the storage consumption and Network data traffic for transmission while enables the progressive transmission of spatial image data. In addition, architecture of searching between clients´ renderer and storage structure at server was provided.