Extensor-based image interpolation

A novel image interpolation method for resolution enhancement of still images is proposed. The approach consists of a nonlinear mapping from pixel index space to color space based on the low-resolution image so that nonintegral pixel indices in a super-sampling can be mapped to colors, i.e., interpolated. This nonlinear mapping is based on an extensor transformation of 2D pixel indices to an, N-dimensional vector space that encodes the Euclidean proximity interrelationships among a neighborhood of N pixels. Experimental results indicate that extensor-based interpolation yields results that are qualitatively superior to classical bilinear and bicubic interpolation, that has important advantages in comparison to edge-directed and optimal-recovery interpolation methods, and that has comparable or lower computational cost.