Blur Length Estimation Based on Image Energy Spectrum Statistics
In order to resolve the non-smooth blur problem for coded exposure imaging, this paper proposes an
automatically motion blur estimation method based on image energy spectrum statistics, and expands
successfully this method to estimate motion blur length for traditional motion blurred images. This
paper finds that the residual sums of squares of polynomial fitness result of the deblurred image
energy spectrum statistics can reach the minimum, only using correct blur length in the
deconvolution process. Given an initial value, using simulated annealing algorithm to implement the
iteration, the correct blur length can be obtained automatically in a very short time. Both the real
and simulated experiment results demonstrate the effectiveness and robustness of the proposed
method.