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.