By Topic

Adaptive combination of linear predictors for lossless image compression

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
$31 $31
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

3 Author(s)
Dong, G. ; Dept. of Electron. Eng., La Trobe Univ., Bundoora, Vic., Australia ; Ye, H. ; Cahill, L.W.

Lossless image coding is an essential requirement for medical imaging applications. Lossless image compression techniques usually have two major components: adaptive prediction and adaptive entropy coding. The paper is concerned with adaptive prediction. Recently, several researchers have studied prediction schemes in which the final prediction is formed by a combination of a group of subpredictors. The authors present an overview of this new type of prediction technique. They show that the basic principle of adaptive predictor combination has been extensively studied and applied to many science and engineering problems. They then describe their own combination scheme, which is based on the estimation of the local prediction error variance. Experimental results show that the compression performance of the algorithms that employ this new type of predictor is consistently better than that of state-of-the-art algorithms

Published in:

Science, Measurement and Technology, IEE Proceedings -  (Volume:147 ,  Issue: 6 )