Blind estimation of motion blur kernel parameters using Cepstral domain and Hough transform


Motion blur results when the scene is not static and image being recorded changes during the recording due to long exposure or motion. Because of motion blur projected image is smeared over the sensor according to the motion. Motion blur PSF is characterized by two parameters, namely blur direction and blur length. Faithful Restoration of the motion blurred image requires correct estimation of these parameters. In this paper we present a Hough transform based motion direction estimation under spatially variant condition. The blur direction is identified using Hough transform of the fourth bit plane of the modified cepstrum to detect the orientation of line in the log magnitude spectrum of the blurred image. Experiments performed on simulated motion blurred image showed that Compare to already existing Hough transform method it successfully estimate PSF parameters even without any preprocessing steps. The blur length is found by rotating the spectrum of the blurred image in the estimated direction then by collapsing the 2-D cepstrum in to 1-D cepstrum and finally by taking the inverse Fourier transform and finding the first negative value. These parameters are then used to restore the images.

DOI: 10.1109/ICACCI.2014.6968241

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@article{Shah2014BlindEO, title={Blind estimation of motion blur kernel parameters using Cepstral domain and Hough transform}, author={Mayana J. Shah and Upena D. Dalal}, journal={2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)}, year={2014}, pages={992-997} }