Normalized Weighting Schemes for Image Interpolation Algorithms

Image interpolation algorithms pervade many modern image processing and analysis applications. However, when their weighting schemes inefficiently generate very unrealistic estimates, they may negatively affect the performance of end-user Therefore, in this work, author introduced four based on some geometric shapes for digital operations. Moreover, quantity used to express extent each shape’s weight was normalized area, especially sums areas exceeded a unit square size. The are minimum side-based diameter (MD) regular tetragon, hypotenuse-based radius (HR), virtual pixel length-based height area triangle (AT), length circle (AC). At smaller scaling ratio, algorithm HR scheme scored highest at 66.6% among non-traditional presented. higher AC scheme-based presented, and, here, its quality generally superior or comparable images interpolated by both traditional algorithms.