Method to Improve Accuracy of PSF parameters of Motion Blur Images using Window Functions
Accurate estimation of the point spread function(PSF)is crucial for restoring blurry images caused by motion blur.This paper proposes a method using window functions to improve the accuracy of PSF parameter estimation and eliminate the interference from the central bright line in the spectrogram on the blurred-angle estimation.To achieve this,two-dimensional discrete Fourier transform and logarithmic operation are performed on the motion-blurred image,followed by the calculation of the power spectrogram.Thereafter,the Hanning window function is added to the spectrogram,and the image is processed using median filtering smoothing and binary transformation processing,in combination with morphological algorithm and Canny operator edge detection.Finally,the fuzzy direction is obtained using the Radon transform.Based on the blurred-direction results,the spectrogram of the motion-blurred image is processed by Radon transform in the direction of the blur angle.The distance between the negative peaks is analyzed to obtain the dark fringe spacing,and the blur length is calculated according to the relation between the dark fringe spacing and the blur length.This completes the estimation of the two point spread function parameters.Comparing the proposed algorithm with existing ones,the results show an improvement in the accuracy of parameter estimation,and a reduction in ringing and artifact phenomena generated during restoration.The proposed method makes full use of image information,and is easy to operate.
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