An image is modeled by a two-parameter stochastic process generated by splitting a pixel into a block of 2 X 2 pixels thereby obtaining a higher resolution image. This sequential reproduction process is achieved by using a sequence of random variables as multipliers. In the analysis of image structure we apply the model in the reverse order, i.e. estimate the sequence of random variables which generates the image. The size of matrices representing the stochastic processes show a pyramidal structure when increasing or decreasing the resolution. The features characterizing an image are provided by analysis of the properties of estimated stochastic processes at each level of the pyramid, and by comparison of properties characteristic of consecutive levels of the pyramid. As a byproduct of this image structure analysis, our approach suggests a new method for data compression.
Y. Y. Zeevi,
"A Pyramid Of Image Generating Functions", Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); doi: 10.1117/12.976513; https://doi.org/10.1117/12.976513