Title :
Predictive source coding techniques using maximum likelihood prediction for compression of digitized images
Author :
Kanefsky, Morton ; Fong, Chung Bin
fDate :
9/1/1984 12:00:00 AM
Abstract :
A predictive compression technique is examined, using maximum likelihood prediction of the image pixel based on the Markov mesh model, that encodes the differences via Gordon block-bit-plane (GBBP) encoding. The procedure is very efficient in that it requires a bit rate near the entropy of the source. For images with many quantization levels, maximum likelihood prediction can be cumbersome to implement. Thus, a suboptimal procedure called differential bit-plane coding (DBPC) is investigated. This is easily implemented, even for a large number of quantization levels, and is reasonably efficient.
Keywords :
Image coding; Markov processes; Prediction methods; maximum-likelihood (ML) estimation; Biomedical computing; Bit rate; Entropy; Image coding; Image storage; Pixel; Predictive models; Pulse modulation; Quantization; Source coding;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1984.1056953