A class of operators based on linear statistical models has been previously developed. The theory of experimental design-based operators - in general, the two-way analysis of variance and specifically Latin Squares designs specified previously - are extended here. Both global and local robust statistical mask texture/extractor operators/object detectors are developed and examined for significance with regard to parallel implementation on a pyramidal architecture. Possible real-time systolic array implementations are considered. Computer experiments using real-world noisy images and simulation results of a pyramidal processing architecture are shown to verify the theory and compare the performance measures of the new class of mask-operators with a more standard class of variance sensing.