Title
Two-dimensional optimal algorithms for image compression using ARMA predictors
Abstract
Adaptive differential pulse code modulation has been extensively used in image data compression due to its relative implementational simplicity. It has also been demonstrated that the use of backward adaptive autoregressive moving average (ARMA) predictors in differential encoding of images lead to subjective improvements in the edge performance. Algorithms using constant convergence factors have been applied to adapt the coefficients of the adaptive predictor. Recently, two-dimensional algorithms using optimized convergence factors have been proposed and investigated. In this paper, two of these algorithms are used to determine the backward adaptive prediction filter coefficients. Simulations and comparative results using both autoregressive (AR) and ARMA predictors show significant objective and subjective improvements when the algorithms using optimum convergence factors are used.
Publication Date
12-1-1994
Publication Title
Proceedings - IEEE International Symposium on Circuits and Systems
Volume
2
Number of Pages
613-616
Document Type
Article; Proceedings Paper
Identifier
scopus
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0028554096 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0028554096
STARS Citation
Ghosh, Shomit M. and Mikhael, Wasfy B., "Two-dimensional optimal algorithms for image compression using ARMA predictors" (1994). Scopus Export 1990s. 82.
https://stars.library.ucf.edu/scopus1990/82