Fuzzy-adapted linear interpolation algorithm for image zooming

This work presents a novel fuzzy linear interpolation algorithm with application in image zooming. Fuzzy logics are employed to derive suitable weights for the neighboring samples in the interpolation formulae. By considering local gradients to calculate the weights, the accuracy of the interpolated value is improved. Additionally, a modification of the proposed algorithm based on the interpolation error theorem is developed to deal with images containing ridges and valleys. Both quantitative results obtained by measuring the peak signal-to-noise ratio (PSNR) and perceptual observations assessed the superior performance of the proposed algorithm and its modified version with respect to the state-of-the-art interpolation methods.