The inverse problem of image restoration to remove noise and blur in an observed image was extensively studied in the last\ntwo decades. For the case of a known blurring kernel (or a known blurring type such as out of focus or Gaussian blur), many\neffective models and efficient solvers exist.However when the underlying blur is unknown, there have been fewer developments for\nmodelling the so-called blind deblurring since the early works of You and Kaveh (1996) and Chan and Wong (1998). A major\nchallenge is how to impose the extra constraints to ensure quality of restoration. This paper proposes a new transform based\nmethod to impose the positivity constraints automatically and then two numerical solution algorithms. Test results demonstrate\nthe effectiveness and robustness of the proposed method in restoring blurred images.
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