In this paper, an effort is made to propose an effective image super resolution (SR) approach to recover a high resolution (HR) image from a single low resolution (LR) image. This approach is based on an iterative back projection (IBP) method with the edge preserving infinite symmetric exponential filter (ISEF) and difference image. Amalgamation of ISEF and difference image provides high frequency information. This approach is applied on different type of images and compared results with different existing image SR approaches. Simulation results demonstrate that proposed approach can more precisely enlarge the LR image. This proposed approach decreases mean square error (MSE) and mean absolute error (MAE) and increases the peak signal-to-noise ratio (PSNR) significantly compared to other existing approaches.
Multi-example feature-constrained back-projection method for image super-resolution
