A Log-Polar Interpolation Applied to Image Scaling

Abstract

This paper proposes a bio-inspired interpolation algorithm suitable for image scaling. A log-polar neighbor model is adopted, utilizing the feature of applying larger weights to pixels at the center of the interpolation region and logarithmically decreasing weights to pixels away from the center. The interpolation is performed in the Cartesian plane without requiring the full transformation of the image to the log-polar plane. Experiments show that in both visual comparisons and quantitative analysis, the results extracted by the proposed log-polar neighbor model are better than those extracted from pixel repetition, bilinear and bicubic interpolation.