An image compression method for spatial search

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...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on image processing 2000-03, Vol.9 (3), p.357-365
Main Authors: Pajarola, R., Widmayer, P.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Compressed
Compressing
Compression algorithms
Computer science
Exact sciences and technology
Geographic Information Systems
Image coding
Image processing
Image retrieval
Image storage
Information retrieval
Information, signal and communications theory
Queries
Query processing
Raster
Satellites
Searching
Signal processing
Spatial indexes
Telecommunications and information theory
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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 spatial index structure to guide a spatial search. In response to a window query, our algorithm delivers a compressed partial image, or the exact uncompressed requested image region. In addition to the support of spatial queries on compressed continuous tone images, the new compression algorithm is even competitive in terms of the compression ratio that it achieves, compared to other standard lossless compression techniques.
ISSN:1057-7149
1941-0042
DOI:10.1109/83.826774