Hexagonal pixel-array for efficient spatial computation for motion-detection pre-processing of visual scenes

Motion-detection, edge-detection, and orientation-detection often require spatial computation of the light intensity difference between neighboring pixel cells. Pre-processing the image at the retinal level can improve the computational efficiency when the parallel processing can be achieved naturally by the spatial arrangement of the pixel-array. Pixel-arrays that require spatial pre-processing computation have different geometric constraints than plain pixel-arrays that do not require such local computation. Our analysis shows that geometric optimization of pixel-arrays can be achieved by using hexagonal arrays over rectilinear arrays. Hexagonal arrays improve the packing density, and reduce the complexity of the spatial computation compared to rectilinear square and octagonal arrays. They also provide geometric symmetry for efficient computation not only at the contiguous neighboring cell level, but also at the higher-order neighboring cell level. The light intensity difference at the higher-order cell level is used to compute the first-order and second-order time-derivatives for velocity and acceleration detections of the visual scene, respectively. Thus, hexagonal arrays increase the computational efficiency by using a symmetric configuration that allows pre-processing of spatial information of the visual scene using hardware implementations that are repeatable in all higher-order neighboring pixels.