By Topic

Compression of map images by multilayer context tree modeling

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kopylov, Pavel ; Univ. of Joensuu, Finland ; Franti, P.

We propose a method for compressing color map images by context tree modeling and arithmetic coding. We consider multicomponent map images with semantic layer separation and images that are divided into binary layers by color separation. The key issue in the compression method is the utilization of interlayer correlations, and to solve the optimal ordering of the layers. The interlayer dependencies are acquired by optimizing the context tree for every pair of image layers. The resulting cost matrix of the interlayer dependencies is considered as a directed spanning tree problem and solved by an algorithm based on the Edmond's algorithm for optimum branching and by the optimal selection and removal of the background color. The proposed method gives results 50% better than JBIG and 25% better than a single-layer context tree modeling.

Published in:

Image Processing, IEEE Transactions on  (Volume:14 ,  Issue: 1 )