A New Study of Blind Deconvolution with Implicit Incorporation of Nonnegativity Constraints

Ke Chen, Simon P. Harding, Bryan M. Williams, Yalin Zheng
2015 International Journal of Computational Mathematics  
The inverse problem of image restoration to remove noise and blur in an observed image was extensively studied in the last two decades. For the case of a known blurring kernel (or a known blurring type such as out of focus or Gaussian blur), many effective models and efficient solvers exist. However when the underlying blur is unknown, there have been fewer developments for modelling the so-called blind deblurring since the early works of You and Kaveh (1996) and Chan and Wong (1998). A major
more » ... allenge is how to impose the extra constraints to ensure quality of restoration. This paper proposes a new transform based method to impose the positivity constraints automatically and then two numerical solution algorithms. Test results demonstrate the effectiveness and robustness of the proposed method in restoring blurred images.
doi:10.1155/2015/860263 fatcat:npzns6j3avh7dhkk53clfrtele