Title :
Identification of Motion Blurred Parameter by using T-norm Operator
Author :
Zhang, Ting-Ting ; Xu, Gang
Author_Institution :
North China Electr. Power Univ., Beijing
Abstract :
Motion blur is one of common blurs that degrades images. Restoration of image is highly dependent on estimation of motion blur parameters. In this paper it has presented a novel algorithm (FSA) to estimate linear motion blur parameters such as direction and extend by using radon transform to find direction and t-norm operator to find its extend. The method was tested on a wide range of different type of standard images that were degraded. Compared to AR model algorithm, the algorithm´s robustness and precision in noisy images is improved greatly. Though SNR is rather low, it still gets highly satisfactory result.
Keywords :
Radon transforms; image motion analysis; image restoration; mathematical operators; parameter estimation; Radon transform; image degradation; image restoration; motion blurred parameter identification; t-norm operator; Cybernetics; Degradation; Educational institutions; Frequency estimation; Fuzzy sets; Image restoration; Machine learning; Motion estimation; Parameter estimation; Robustness; Blur extend; Fuzzy set algorithm; Radon transform; Robustness;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370402