ABSTRACT
Fourier Transformation has already been described at the beginning of Chapter 7. Data thinning is based on an assessment which decides that some details of the data are nominally more or less 'important' than others. For audio or visual data this judgement will depend upon the details of human perception. The rules for this are complex and do vary to some extent from one person to another. However experiments have shown that one of the most effective ways to proceed is to convert signals into some form of frequency spectrum and then discard those frequency components that are 'too small to be missed'.
