Modelling magnetic material images with simultaneous autoregressions

This paper presents a novel application of simultaneous autoregressive models to the synthesis of magnetic material images. The effects of using either symmetric or non-symmetric neighbour sets upon the visual and statistical properties of the resulting synthesised images are investigated. The use of a neighbour set whose shape corresponds to the orientations and coarseness of the texture allows the generation of synthetic images of good quality. Also, the size of such a neighbour set is usually smaller than that of the symmetric set required to reach similar modelling accuracy, thereby minimising the computational effort