Identification of blur parameters from motion blurred images
Graphical Models and Image Processing
Motion-Based Motion Deblurring
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blur identification from vector quantizer encoder distortion
IEEE Transactions on Image Processing
An EM algorithm for wavelet-based image restoration
IEEE Transactions on Image Processing
A VQ-based blind image restoration algorithm
IEEE Transactions on Image Processing
Multiple-Image-Based Restoration for Motion Blur with Non-uniform Point Spread Function
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Estimation of the noise variance of uniform linear motion blurred images
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 3
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A motion blur identification scheme is proposed for non-linear uniform motion blurs approximated by piecewise linear models which consist of more than one linear motion component. The proposed scheme includes three modules that are a motion direction estimator, a motion length estimator and a motion combination selector. In order to identify the motion directions, the proposed scheme is based on a trial restoration by using directional forward ramp motion blurs along different directions and an analysis of directional information via frequency domain by using a Radon transform. Autocorrelation functions of image derivatives along several directions are employed for estimation of the motion lengths. A proper motion combination is identified by analyzing local autocorrelation functions of non-flat component of trial restored results. Experimental examples of simulated and real world blurred images are given to demonstrate a promising performance of the proposed scheme.