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Super-resolution images from blurred observations

In this paper, we present a technique for generating a high- resolution image from a blurred image sequence. The image sequence consists of decimated, blurred and noisy versions of the high- resolution image. The high-resolution image is modeled as a Markov random field, and a maximum a posteriori estimation technique is used for image restoration. A fast algorithm based on Fast Fourier Transforms (FFTs) is derived to solve the resulting linear system. Numerical examples are given to illustrate the effectiveness of the method.