A Variational Approach to Moir E Pattern Synthesis

Moir e phenomena occur when two or more images are nonlinearly combined to create a new \superposition image". Moir e patterns are patterns that don't exist in any of the original images but appear in the super-position image as the result of a multiplicative superposition rule. The topic of moir e pattern synthesis deals with creating images that, when superimposed, will reveal certain desired moir e patterns. Conditions ensuring that a desired moir e pattern will be present in the superposition of two images are known, however they do not specify these images uniquely. The freedom in choosing the superimposed images can be exploited to produce various degrees of visibility and ensure desired properties. Performance criteria for the images that measure when one superpo-sition is better than another are introduced. These criteria are based on the visibility of the moir e patterns to the human visual system and on the digitization which takes place when presenting the images on discrete displays. We here propose to resolve the freedom in moir e synthesis by choosing the images that optimize the chosen criteria.