Image interpolation by rational ball cubic B-spline representation and genetic algorithm

In this article a rational ball cubic B-spline representation based image interpolation scheme is proposed with tension parameter to interpolate two dimensional natural images. Genetic algorithm is used to detect the optimal value of tension parameter, so that sum square error is minimum. Comparison among the proposed interpolation scheme and the existing image interpolation techniques in terms of some state-of-the-art image quality metrics with classical Peak Signal-to-Noise Ratio (PSNR), depicts that suggested ball cubic B-spline form produces better results and is more suitable for problems related to image interpolation. (C) 2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V.