The paradigmatic starting point in this book is that, for a given proximal stimulus, the distal organization with the simplest descriptive code is predicted to be perceived. This starting point as such, however, does not yet prescribe which specific coding scheme is to be employed. This has been pointed out by Simon (1972). He compared a number of perceptual coding models (including SIT's), and he found that these models perform about equally well. In the 1960s, a similar finding in mathematics (i.e., the Invariance Theorem; see Chapter 2) brought mathematicians to conclude that the descriptive simplicity paradigm is sufficiently robust to modeling variations to form the basis of promising research. Simon's (1972) equally rightful conclusion, however, was:

Hence, Simon called for a foundation of the specifics of the coding model to be used in perception. These specifics comprise (a) the coding rules that are applied to capture regularity, and (b) the information measure that is applied to quantify complexity. In vision, the regularities to be captured are visual regularities and the information to be measured is structural information. This, however, evokes profound questions:

1. • How to distinguish between visual and nonvisual regularities?

2. • How to measure amounts of structural information?