A context-based adaptive predictor for use in lossless image coding

F. Golchin, K.K. Paliwal
TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications (Cat. No.97CH36162)  
In this paper, we propose a context-based adaptive predictor for use in lossless image coding. Most often, lossless image coders utilize non-adaptive linear predictors for the sake of simplicity and to reduce the complexity of the coder. In DPCM-based lossless image coders, adaptivity can result in significant improvements in the performance. However, adaptive prediction is faced with a number of problems chiefly its extensive computational demands. The predictor proposed in this paper allows
more » ... r a lower computational cost while guaranteeing the stability of the predictor. The Context-Based Adaptive Predictor (CBAP) was found to outperform or at least perform equally as well as the optimum linear predictor for a variety of test images. We should also note that designing an optimum linear predictor requires some knowledge of the image prior to coding while the CBAP requires no such knowledge and operates "on-the-fly" . "The first author is supported in part by a CSIRO Division of Telecomm. and Industrial Physics postgraduate scholarship. 1997 IEEE TENCON -Speech and Image Technologies for Computing and Te1.ecommunications
doi:10.1109/tencon.1997.648520 fatcat:dpvfutwhtrbk5by47hw4svrxwa