Lattice transformations are a class of nonlinear image processing transforms that include mathematical morphology transforms as a subclass. By using a matrix representation lattice transforms may apply results established in minimax algebra a matrix algebra originally developed for operations research. This paper presents a strong decomposition technique for a translation invariant template that is a lattice transform using a minimax matrix approach. The factors of the decomposition correspond to variant templates. This method is particularly suited for implementation on multiple-instruction multiple-data (MIMD) architectures. Since the minimax algebra is a subalgebra of the Air Force image algebra which in turn encompasses mathematical morphology this technique provides another tool for template decomposition which in particular can be applied to morphology transforms.