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The above-described methods of detecting repetitive occurrences of pattern and treating them as redundancies that one can get rid of are mainly used to compress data. For the sake of speed, bandwidth or storage space efficiency, they try to cut off as much as possible while derogating readability as little as necessary.

However, the focus in the present case is a different one. The principle interest is not a reduction of data but rather a concentration. The architect should be given a tool that allows him or her to design in great complexity and in an incredible richness, while only having a small number of strings to pull. Designing in the frequency domain does mean not to specify the position in time and space of every instance but it assumes always a continuity. One data point implies already a pattern. What works for one (e.g. sound or stock market prices) or two-dimensional data – illustrated in the present work with the example of wood grain textures – is without further ado scalable to three or more dimensions. Rhythms in space of matter and void can be analyzed and synthesized, orchestrating spatial patterns.

Fig. 11 Average image of all the 144 samples of Fig. 1

Fig. 12 Average image enhanced to cover the entire contrast range

Fig. 13 Same reduction ratio applied to the number of pixels