A new convolution-based image interpolation method is presented, whose kernel function is designed via blending some well-known kernels. The new kernel is a better approximation to sinc function both in the space domain and the frequency domain. Comparative experiments with several polynomial spline type algorithms indicate that our approach exhibits a significant improvement in image quality.