Spatial indexing into compressed raster images: how to answer range queries without decompression

Abstract

The maintenance of large raster images under spatial operations is still a major performance bottleneck. For reasons of storage space, images in a collection such as satellite pictures in geographic information systems, are maintained in compressed form. Instead of performing a spatially selective operation on an image by first decompressing the compressed version, we propose to perform queries directly on the compressed version of the image. We suggest a compression technique that allows for the subsequent use of a data structure to guide a spatial search. In response to a range query, our algorithm delivers a compressed partial image. Experiments show that the new algorithm supports spatial queries on satellite images efficiently. In addition it is even competitive in terms of the compression that it achieves.