Image Enlargement Method by a Quadratic Interpolation Kernel with Variable Parameters

Abstract

This paper presents a quadratic kernel with four variable parameters for image enlargement. The proposed kernel can generate peak and valley information of the signals by considering the characteristics of the image and by changing these parameters. Moreover, as the proposed kernel is the extension of the linear interpolation and the nearest-neighbor interpolation, the forms of the proposed kernel are also used selectively depending on the characteristics of signal points which are used for parameter estimation. The various standard images are enlarged using the proposed kernel, and the performance of the proposed kernel is evaluated with MSE of the enlarged images. It has been shown that the performance of the proposed kernel is better than the other methods, such as the cubic interpolations that are often used in image processing.