Motion blur identification in noisy images using fuzzy sets

Motion blur is one of the most common blurs that degrades images. Restoration of such images are highly dependent to estimation of motion blur parameters. Many researchers have developed algorithms to estimate linear motion blur parameters. These algorithms are different in their performance, time complexity, precision and their robustness in noisy environments. In this paper we have presented a novel algorithm to estimate linear motion blur parameters such as direction and extend by using Radon transform to find direction and fuzzy set concepts to find its extend. The most benefit of this algorithm is its robustness and precision in noisy images. Our method was tested on a wide range of different type of standard images that were degraded with different directions (between 0 degrees and 180 degrees) and different motion lengths (between 10 to 50 pixel). Experimental results showed in average S N R > 22 db that is highly satisfactory.