Multi-Orientation Estimation: Selectivity and Localization

Filtering of an image with rotated versions of an orientation selective filter yields a set of images which can be stacked to form an orientation space. Orientation space provides a means of analyzing overlapping and touching anisotropic textures. A set of rotated k order directional derivatives yields a discrete orientation space, which allows interpolation. Next we apply a deconvolution scheme that results in improved orientation selectivity. This scheme allows decomposition of noisy multi-orientation patterns.