A reciprocal-wedge transform (RWT) for space-variant sensing is presented. The RWT preserves linear features and facilitates translations in images. A concise RWT matrix representation and its applications to geometric transformations in the image plane are described. Like the log-polar transform, the RWT facilitates space-variant sensing, which enables effective use of variable-resolution data and the reduction of the total amount of sensory data. The RWT yields anisotropic variable resolution, which provides an alternative for active sensing when the shift of attention is primarily in one dimension. A projective model of the RWT is delineated and a hardware RWT projection camera is proposed. As an application of the RWT, the problem of road following in robot navigation and some initial experimental results are demonstrated.
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