The key issue to restore the defocus blurred image is how to choose a degradation model of blurred image. Based on the
fractional Fourier transform (FrFT) combining with the clarity-evaluation-function, we present an approach for the
restoration of defocus blurred image. This method constructs a defocused imaging model based on FrFT and estimates
the lost phase signals from the intensity signals by an iterative phase retrieval approach, in which the sharp restored
image can be acquired by implementing inverse FrFT on complex image signal made from the estimated phase signals
and intensity signals. Using this model combing with the clarity-evaluation-function, the FrFT order can be changed
adaptively. Consequently, the sharper image can be obtained in the end. Experimental results show the effectiveness, the
robustness, and the low complexity of this approach, which make it more suitable for real-time environment.
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