Data Compression Techniques for Maps
Abstract
The efficiencies of various data compression techniques as applied to color maps are compared. These color maps have certain special characteristics such as large homogeneous regions and fine detail such as lines and lettering. The color maps are first classified using the K means clustering algorithm with neighborhood classification. Three techniques are investigated - contour, quadtree and run-length coding. The run-length coding algorithm is modified to allow wrap around of runs. A modification of the standard binary image quadtree compression algorithm for color images is introduced. In quadtree coding a modified eldest-son eldest younger sibling quadtree is used to reduce memory requirement in storing the quadtree. Lempel-Ziv compression is applied to the classified and unclassified images as also to the output of the compression algorithms. The algorithms will be compared on the compression ratios achieved.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1989
- Accession Number
- ADA508992
Entities
People
- A. Bermúdez MartÃnez
- H. Barad
- H. Potlapalli
- J. Pollard
- Jason T. Ryan
- M. C. Lohrenz
- M. Y. Jaisimha
Organizations
- Tulane University of Louisiana