A method to improve accuracy of parameter identification for single image blurred by uniform linear motion

To search a parameter identification method with high accuracy for single image blurred by uniform linear motion, a few of available algorithms, such as cepstral analysis, Radon transform, image derivative, autocorrelation-based and detect function-based, were used to simulate the performance of identification and to compare the results of parameter identification, especially for parameters of motion direction and blur length. It was found that cepstral analysis algorithm could identify motion direction with the best accuracy, while autocorrelation-based method could identify blur length with the best accuracy. Based on that analysis, it could be suggested that the scheme combined of cepstral analysis with autocorrelation-based algorithms would get high accurate estimation when single image is just blurred by uniform linear motion.