Estimates for information quantity in probability model in image encoding

Abstract

Upper bounds are obtained for the amount of information in functional classes with initial uncertainty. These classes are similar to the classes of images with bounded variance. We use the probability model of the theory of information complexity. Unlike the case of classes $KH_{0}^{ α}$ , it turns out that, in this case, the method of differential pulse-code modulation does not give any advantage as compared to the deterministic case.