Due to the development of multimedia hardware and computer devices, single-image super resolution has recently become a hot topic. The main concept of super resolution is to obtain a high-resolution image from a low-resolution one, and the former should look like it had been acquired with a sensor having the resolution of the up scaled image or, at least, present a "natural" texture. Most existing single-image super resolution techniques upscale a low-resolution image by either spatial-domain based or wavelet-domain based algorithms. Edge information in the spatial domain can be detected and enhanced to construct a sharp high-resolution image while in the wavelet domain, the support of filters to model the regularity of natural images is exploited. The proposed algorithm combines the advantages of both spatial-domain based and wavelet-domain based algorithms where the back-projection technique is adopted to minimize the reconstruction error with an efficient iterative procedure. Comparing with conventional image interpolation techniques, simulation results show that the proposed algorithm is considerably superior in both objective and subjective terms. Finally, for lowering down the hardware cost, some improvement is presented that can properly reduce the scan lines according to the limit of the input buffer.