Least-squares Optimal Interpolation for Fast Image Super-resolution
Andrew Gilman, Donald G. Bailey, Stephen Marsland · 2010
Image super-resolution is generally regarded as consisting of three steps - image registration, fusion, and deblurring. This paper presents a novel technique for resampling a non-uniformly sampled image onto a uniform grid that can be used for fusion of translated input images. The proposed method can be very fast, as it can be implemented as a finite impulse response filter of low order (10th order results in good performance). The technique is based on optimising the resampling filter coefficients using a simple image model in a least squares fashion. The method is tested experimentally on a range of images and shown to have similar results to that of a least-squares optimal filter. Further experimental comparisons are made against a number of methods commonly used in image super-resolution that show that the proposed method is superior to these.