Image Super-Resolution Using Image Registration and Neural Network Based Interpolation

This paper presents a new algorithm for image super resolution using image registration and neural network. Our method breaks out the limit of registration-based methods which uses the bicubic interpolation to estimate the missing pixel values. Since bicubic method cannot interpolate these pixels exactly, we need more low-resolution frames at input to increase the super-resolution performance. Our algorithm uses a multi-layer perceptron to get better interpolation. This solution leads to higher quality at high-resolution output image without increasing the input number. Experimental results show that our method improves the performance of image super resolution.